RESEARCH PAPERS

genetic algorithm research papers 2012




A biased random-key genetic algorithm for the Steiner triple covering problem
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ABSTRACT We present a biased random-key genetic algorithm (BRKGA) for finding small covers of computationally difficult set covering problems that arise in computing the 1-width of incidence matrices of Steiner triple systems. Using a parallel implementation of the 

A Receding Horizon Genetic Algorithm for Dynamic Resource Allocation: A Case Study on Optimal Positioning of Tugs
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This paper presents a receding horizon genetic algorithm (RHGA) for dynamic resource allocation. The algorithm combines methods from control theory and computational intelligence to simultaneously solve the problems of (i) coordinated control of resources,(ii 

Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach
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Aggregate production planning is associated with the determination of inventory, production and work force levels to consider fluctuating demand needs over a planning horizon, which ranges from six months up to a year. Typically, the planning horizon includes the next 

Valuing Water Quality Trade offs Using an Integrated Economic-Biophysical Hybrid Genetic Algorithm
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ABSTRACT This study evaluates the trade off between agricultural production and water quality using an integrated economic-biophysical hybrid genetic algorithm. We apply a multi-input, multi-output profit-maximization model to detailed farm-level production data from the 

A Hybrid Generational Genetic Algorithm for the Periodic Vehicle Routing Problem with Time Windows
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ABSTRACT We propose the first generational genetic algorithm for the periodic vehicle routing problem with time windows. The algorithm takes the form of a hybrid metaheuristic in which a set of neighborhood-based meta-heuristics cooperate with the population evolution 

Adaptive Genetic Algorithm method for Crystal Structure Prediction and Materials Discovery
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 design and accelerating the pace of technological advances. Page 8. Genetic Algorithm (GA) ? GA is an optimization strategy inspired by the Darwinian evolution process.  Grain Boundary Structures (510) Tilt boundary Page 13. Genetic Algorithm (GA) 13 N p final structures 

A Genetic Algorithm for Alignment of Multiple DNA Sequences
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ABSTRACT This paper presents a new genetic algorithm based solution to obtain alignment of multiple DNA molecular sequences. Multiple Sequence alignment is one of the most active ongoing research problems in the field of computational molecular biology. Sequence 

Application of Genetic Algorithm (GA) Approach in the Formation of Manufacturing Cells for Group Technology
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ABSTRACT This paper is about minimizing intercellular movements of parts for the formation of manufacturing cells using GA approach. GA is a search technique based on the process of biological evolution and has been applied as an optimization method for the formation of 

Hybrid Genetic Algorithm with PSO Effect for Combinatorial Optimization Problems
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ABSTRACT In engineering field, many problems are hard to solve in some definite interval of time. These problems known as combinatorial optimisation problems are of the category NP. These problems are easy to solve in some polynomial time when input size is small 

A Survey on Software Testing Techniques using Genetic Algorithm
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ABSTRACT The overall aim of the software industry is to ensure delivery of high quality software to the end user. To ensure high quality software, it is required to test software. Testing ensures that software meets user specifications and requirements. However, the field of 

Optimal Design of a Cogeneration System in a Kraft Process using Genetic Algorithm
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Cogeneration is one of the best methods for energy saving which makes a better use of fuels by using recovered heat and producing heat and power simultaneously. In this study, the implementation of a cogeneration system (CHP) integrated with an industrial pulp and 

A study using Genetic Algorithm and Support Vector Machine to find out how the attitude of training personnel affects the performance of the introduction of Taiwan
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After entering knowledge economy era, human resource has become one of the most important manufacturing elements of an enterprise, hence, human resource incubation has become one of the important jobs of enterprise development. However, most of the 

An Assessment of Efficient Output of a Digital Circuit Using Genetic Algorithm
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ABSTRACT –The rapid growth of Digital devices increases the interest of researchers in this area. In this field, Digital circuit is an important part of providing better services. There is a crucial algorithm called Genetic Algorithm can be use in order to solve the problem of 

Electricity Distribution Scheduling For Gaza Strip Using Genetic Algorithm
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This paper presents a genetic algorithm based approach to the scheduling of electricity distribution. Gaza strip challenges shortage of electricity power. Electricity Distribution Company overcomes this shortage by dividing the cities into sub-regions and providing 

Feature Selection for Classification of Remote Sensed Hyperspectral Images: A Filter approach using Genetic Algorithm and Cluster Validity
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ABSTRACT In this paper, we investigate the advantages of using feature selection approaches for classification of remote sensed hyperspectral images. We propose a new filter feature selection approach based on genetic algorithms (GA) and cluster validity 

Biased random-key genetic algorithm for bound-constrained global optimization
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ABSTRACT Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a biased random-key genetic algorithm for finding approximate solutions for continuous global optimization problems 

Genetic Algorithm Based Tuning of Fixed Bias PID Controller for a Nonlinear Constant Temperature Water Bath under Load Disturbances
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ABSTRACT The present work gives experimental results for the control of a continuously stirred constant temperature nonlinear water bath under constant flow. A real time PID controller taken with a fixed bias voltage has been used and tuned by Genetic Algorithm. Genetic 

Hybrid Genetic Algorithm Optimisation of Distribution Networks-A Comparative Study
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This chapter focuses on the second of a three-stage, integrated methodology for modeling and optimising distribution networks (DN) based on hybrid genetic algorithms (HGA). The methodology permits any combination of transportation and warehousing costs for 

An analysis of the solution quality of the simple genetic algorithm
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ABSTRACT We introduce a probabilistic worst case bound on the solution quality for the simple genetic algorithm. Given a probability and number of iterations a simple genetic algorithm has performed we show how to bound the distance between the best solution found and 

An application of genetic algorithm method for solving patrol manpower deployment problems through fuzzy goal programming in traffic management system: a case
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This article demonstrates a fuzzy goal programming (FGP) approach with the use of genetic algorithm (GA) for proper deployment of patrol manpower to various road–segment areas in urban environment in different shifts of a time period to deterring violation of traffic rules 

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building
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ABSTRACT A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and 

Spatial aggregation and compactness of census areas with a multiobjective genetic algorithm: a case study in Canada
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ABSTRACT The paper focuses on a case study of delineating census tracts (CTs) in the Census Metropolitan area of London, Ontario, Canada. The procedure for defining the actual pattern of CTs by a local committee and Statistics Canada has involved such 

Using Multiobjective Genetic Algorithm and Multicriteria Analysis for the Production Scheduling of a Brazilian Garment Company
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The Brazilian garment industry has been forced to review its production processes due to the competition against Asiatic countries like China. These countries subsidize the produc- tion in order to generate employment, which reduces the production cost. This competition 

Optimal Policy for the Replacement of Industrial Systems Subject to Technological Obsolescence–Using Genetic Algorithm
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ABSTRACT The technological obsolescence of industrial systems is characterized by the existence of challenger units possessing identical functionalities but with improved performance. This paper aims to define a new approach that makes it possible to obtain 

Damage Detection in Beam Structures using a Combined Genetic Algorithm and Nonlinear Optimisation System
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ABSTRACT In this paper, a combined genetic algorithm and non-linear optimisation system is designed and used in the identification of structural damage of a cantilever isotropic beam regarding its location and severity. The vibration-based features, both natural frequencies 

Implementation of Genetic Algorithm in Predicting Diabetes
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ABSTRACT Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily compressible to humans. Data Mining represents a process developed to examine large amounts of data routinely collected. The term also refers to a collection of 

Performance analysis of the partial use of a local optimization operator on the genetic algorithmfor the Travelling Salesman Problem
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Background: The Travelling Salesman Problem is an NP-hard problem in combinatorial optimization with a number of practical implications. There are many heuristic algorithms and exact methods for solving the problem. Objectives: In this paper we study the 

Genetic algorithm calibration for two objective scheduling parallel jobs on hierarchical grids
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This paper addresses non-preemptive offline scheduling parallel jobs on a Grid. We consider a Grid scheduling model with two stages. At the first stage, jobs are allocated to a suitable Grid site, while at the second stage, local scheduling is independently applied to 

Denial-of-Service Attack Detection Using Genetic-Based Algorithm
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 In this paper idea for use of a Genetic Algorithm (GA) based approach, for generation of rules to detect DoS attacks on the system is proposed. A short general idea of Intrusion Detection System, genetic algorithm and related detection techniques is provided. 

A hybrid genetic algorithm and particle swarm optimization based fuzzy times series model for TAIFEX and KSE-100 forecasting
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ABSTRACT In this paper we proposed a new evolutionary fuzzy time series forecasting model for Taiwan Futures Exchange (TIAFEX) and Karachi Stock Exchange (KSE-100) forecasting. Our proposed method is based on two-factor high order fuzzy logical relation groups. A 

Low Power NOC Process Element Mapping Using Genetic Algorithm
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ABSTRACT Network on chip process elements mapping is a NP-complete problem, and the results will directly affect the chip's power and other properties, so how to obtain a low power mapping solution efficiently is a difficult problem faced by NOC designers. Based on the 

Calibration of Xinanjiang model parameters using hybrid genetic algorithm based fuzzy optimal model
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ABSTRACT Conceptual rainfall–runoff (CRR) model calibration is a global optimization problem with the main objective to find a set of optimal model parameter values that attain a best fit between observed and simulated flow. In this paper, a novel hybrid genetic 

A Cooperative Ant Colony Optimization-Genetic Algorithm approach for construction of energy demand forecasting knowledge-based expert systems
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Page 1. A Cooperative Ant Colony Optimization-Genetic Algorithm approach for  Li and Su [47] proposed a hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model for forecasting energy demand of buildings. 

Load–balanced CDS construction in wireless sensor networks via genetic algorithm
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A Connected Dominating Set (CDS) is used as a virtual backbone for Wireless Sensor Networks (WSNs). Most existing works focus on a Minimum CDS (MCDS), ak–connect m– dominating CDS, a minimum routing cost CDS or a bounded–diameter CDS, ignoring the 

Genetic Algorithm for Innovative Device Designs in High-Efficiency III–V Nitride Light-Emitting Diodes
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Light-emitting diodes are becoming the next-generation light source because of their prominent benefits in energy efficiency, versatility, and benign environmental impact. However, because of the unique polarization effects in III–V nitrides and the high 

Comment on Quantum Multiplexer Designing and Optimization applying Genetic Algorithm
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ABSTRACT We have noticed that many fundamental laws and rules of quantum-circuit are violated in a work published in International Journal of Computer Science Issues . The authors of this published work presented a quantum multiplexing circuit which is 

Feasible Solution Constraint-Handling Genetic Algorithm to Power Economic Dispatch
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ABSTRACT –This paper presents a new constraint-handling genetic approach based on preserving feasibility of solutions of the economic dispatch problem. A realcoded genetic algorithm is implemented to minimize the active power generation cost while satisfying 

An integer linear programming formulation and genetic algorithm for the maximum set splitting problem
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ABSTRACT We consider the maximum set splitting problem (MSSP). For the first time an integer linear programming (ILP) formulation is presented and validity of this formulation is given. We propose a genetic algorithm (GA) that uses the binary encoding and the 

Secret Key Encryption Algorithm Using Genetic Algorithm
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ABSTRACT In today's information age, information sharing and transfer has increased exponentially. Security, integrity, non-repudiation, confidentiality, and authentication services are the most important factors in information security. In now days the security of 

Forecasting space–time variability of wave heights in the Bay of Bengal: a genetic algorithmapproach
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ABSTRACT The present work employs a genetic algorithm to carry out wave height forecasting in the Bay of Bengal. The use of empirical orthogonal function analysis allows the spatial extending of the forecast to the entire basin. The chaotic nature of the process limits the 

Modelling Fish Habitat Preference with a Genetic Algorithm-Optimized Takagi-Sugeno Model Based on Pairwise Comparisons
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Species-environment relationships are used for evaluating the current status of target species and the potential impact of natural or anthropogenic changes of their habitat. Recent researches reported that the results are strongly affected by the quality of a data set used. 

Genetic Algorithm Sequential Monte Carlo Methods For Stochastic Volatility And Parameter Estimation
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ABSTRACT Particle filters are an important class of online posterior density estimation algorithms. In this paper we propose a real coded genetic algorithm particle filter (RGAPF) for the dual estimation of stochastic volatility and parameters of a Heston type stochastic 

Forecast Global Carbon Dioxide Emission By Use of Genetic Algorithm (GA)
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ABSTRACT Global climate change due to CO2 emissions is an issue of international concern that primarily attributed to fossil fuels. In this study, Genetic Algorithm (GA) is used for analyzing world CO2 emission based on the global energy consumption. Linear and non- 

Web Usage Data Clustering Using Improved Genetic Fuzzy C-Means Algorithm
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 attempts have adapted the C-means clustering algorithm as well as genetic algorithms to find sets of clusters .In this paper; we have proposed a new framework to improve the web sessions' cluster quality from fuzzy c-means clustering using Improved Genetic Algorithm (GA). 

Using a genetic algorithm to optimize the total cost for a location-routing-inventory problem in a supply chain with risk pooling
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ABSTRACT This paper addresses a problem of designing a multi-echelon supply chain with the single sourcing type and the related inventory systems. We also presents a novel mathematical model considering the risk-pooling, lead time, multi-echelon inventory under 

An experimental study of a hybrid genetic algorithm for the maximum traveling salesman problem
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Purpose In this paper, we consider the maximum traveling salesman problem, a variation of the usual traveling salesman problem, in which the objective is to maximize the cost of a tour of the salesman. The main purpose of this paper is to develop a hybrid genetic algorithm ( 

Application of Genetic Algorithm to Maximise Clean Energy usage for Data Centres
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The communications industry is currently witnessing a continued increase in energy consumption, and this trend is predicted to increase even more in the coming years. This is largely driven by the popularity of the Internet, which continues to attract growing numbers 

hybrid genetic algorithm

A Hybrid Genetic Algorithm for Classification.
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Abstract In this paper we describe a method for hybridizing a genetic algorithm and nearest neighbours classification algorithm. We use the genetic algorithm and a training data set to learn real-valued weights associated with individual attributes in the data set. We

A hybrid genetic algorithm for highly constrained timetabling problems
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Abstract In this paper, we present a powerful hybrid genetic algorithm based around a heuristic timetabling framework. This combines a direct representation of the timetable with heuristic crossover operators to ensure that the most fundamental constraints are never

Hybrid genetic algorithm, simulated annealing and tabu search methods for vehicle routing problems with time windows
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ABSTRACT The Vehicle Routing Problem with Time Windows (VRPTW) involves servicing a set of customers, with earliest and latest time deadlines, with varying demands using capacitated vehicles with limited travel times. The objective of the problem is to service all

A Hybrid Genetic Algorithm For The Vehicle Routing Problem With Time Windows.
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Abstract This paper suggests a new hybrid genetic algorithm for the 2D Euclidean vehicle routing problem with time windows. The natural crossover, proposed for the 2D Euclidean traveling salesman problem, was adopted with some modification in the suggested

Improved wavelet neural network based on hybrid genetic algorithm applicationin on fault diagnosis of railway rolling bearing
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Abstract The method of improved wavelet transform neural network based on hybrid GA (genetic algorithm) is presented to diagnose rolling bearings faults in this paper. Genetic Artificial Neural Networks (GA-ANN) overcomes BP neural network's fault of slow ABSTRACT The GA-P performs symbolic regression by combining the traditional genetic algorithm's function optimization strength with the genetic-programming paradigm to evolve complex mathematical expressions capable of handling numeric and symbolic

A Hybrid Genetic Algorithm for Multiway Graph Partitioning.
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Abstract A hybrid genetic algorithm for multiway graph partitioning is proposed. The algorithm includes an efficient local optimization heuristic. Starting at an initial solution, the heuristic iteratively improves the solution using cyclic movements of vertices. The

A hybrid genetic algorithm for the multidimensional knapsack problem
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Abstract. During the last two decades solving combinatorial optimization problems, using genetic algorithms (GA), has attracted the attention of many researchers. In this paper a strong initial population is created by Dantzig algorithm for solving single knapsack

Optimal power flow based on hybrid genetic algorithm
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Optimal Power Flow (OPF) is one of the main functions of Power Generation Operation and Control. It determines the optimal settings of generating units, bus voltage, and transformer tap and shunt elements in Power System with the objective of minimizing total production

A hybrid genetic algorithm to solve a lot sizing and scheduling problem
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Abstract This paper reports a lot-sizing and scheduling problem, which minimizes inventory and backlog costs of multiple products on M parallel machines with sequence-dependent set-up times over T periods. Problem solutions are represented as product subsets (

An improved genetic algorithm with variable population-size and a PSO-GA based hybridevolutionary algorithm
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Abstract: This paper presents an improved genetic algorithm with variable popnlation-sim (VPGA) inspired by the natural features of the variable size of the population. Based on the VPGA and the particle swarm optimization (F 'SO) algorithms, this paper also proposes a

A parallel hybrid genetic algorithm for multiple protein sequence alignment
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ABSTRACT This paper presents a parallel hybrid genetic algorithm (GA) for solving sum-of- pairs multiple protein sequence alignment. The method is based on a multiple population GENITOR-type GA and involves local search heuristics. It is then extended to parallel to

Hybrid approach for optimal nesting using a genetic algorithm and a local minimizationalgorithm
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Abstract In layout design problems including blank nesting, the positions and directions of layout elements must be determined so as to minimize the total space. It is difficult and computationally time-consuming to find the optimal solution for such layout problems,

Hybrid genetic algorithm and particle swarm optimization for the force method-based simultaneous analysis and design
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Abstract The computational drawbacks of existing numerical methods have forced researchers to rely on heuristic algorithms. Heuristic methods are powerful in obtaining the solution of optimization problems. Although these methods are approximate methods (ie

A hybrid decision tree/genetic algorithm for coping with the problem of small disjuncts in data mining.
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Abstract The problem of small disjuncts is a serious challenge for data mining algorithms. In essence, small disjuncts are rules covering a small number of examples. Due to their nature, small disjuncts tend to be error prone and contribute to a decrease in predictive accuracy.

A New Hybrid Genetic Algorithm for the Job Shop Scheduling Problem with Setup Times.
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Abstract In this paper we face the Job Shop Scheduling Problem with Sequence Dependent Setup Times by means of a genetic algorithm hybridized with local search. We have built on a previous work and propose a new neighborhood structure for this problem which is We describe a general and robust method for identification of an optimal non-linear mixed effects model. This includes structural, inter-individual random effects, covariate effects and residual error models using machine learning. This method is based on combinatorial

A hybrid genetic algorithm for the satisfiability problem
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Abstract: This paper introduces a hybrid genetic algorithm for the satisfiability problem (SAT). This algorithm, called GASAT, incorporates local search within the genetic framework. GASAT relays on a problem specific crossover operator to create new solutions, that are

A hybrid genetic algorithm for logistics network design with flexible multistage model
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ABSTRACT Logistics network plays a key role in building an efficient and flexible logistics system for companies in the global business environment. A lot of research has been conducted in this field. While the researchers treat logistics networks design problem as a

A Hybrid Genetic Algorithm for Minimum Vertex Cover Problem.
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Abstract. Minimum vertex cover problem (MVCP) is an NP-hard problem and it has numerous real life applications. This paper presents hybrid genetic algorithm (HGA) to solve MVCP efficiently. In this paper we have demonstrated that when local optimization

A hybrid genetic algorithm/decision tree approach for coping with unbalanced classes
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Abstract This paper proposes a new approach for coping with the problem of unbalanced classes, where some class (es) is (are) much less frequent than the other (s). The proposed approach is a hybrid genetic algorithm/decision tree system. The genetic algorithm acts as

The Automated Timetabling of University Exams using a Hybrid Genetic Algorithm
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The examination timetable for the University of Nottingham consists of over eight hundred exams scheduled over a period of two weeks, repeated twice a year. Each exam, on average, conflicts with about thirty others while the most conflicting exam, an Inter-Faculty

An extended hybrid genetic algorithm for exploring a large search space
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Abstract Recently, a hybrid methodology for combining genetic algorithms and local search algorithms has received considerable attention. This paper proposes an extended hybrid genetic algorithm to further improve the performance of finding the optimal solution in a

A real-coded hybrid genetic algorithm to determine optimal resin injection locations in the resin transfer molding process
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Abstract: Real number-coded hybrid genetic algorithms for optimal design of resin injection locations for the resin transfer molding process are evaluated in this paper. Resin transfer molding (RTM) is widely used to manufacture composite parts with material and geometric

Development of hybrid model and optimization of metal removal rate in electric discharge machining using artificial neural networks and genetic algorithm
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ABSTRACT The present work is aimed at optimizing the metal removal rate of die sinking electric discharge machining (EDM) by considering the simultaneous affect of various input parameters. The experiments are carried out on Ti6Al4V, HE15, 15CDV6 and M-250.

A hybrid genetic algorithm for the vehicle routing problem with controlling lethal gene
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One of the main obstacles in applying genetic algorithms (GAs) to complex problems has been the high computational cost due to their slow convergence rate. We encounter such a difficulty when we attempt to use the classical GA for vehicle routing problem (VRP). In the

Hybrid genetic algorithm for vehicle routing and scheduling problem
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Abstract: This study aims to solve Vehicle Routing Problem with Time Windows (VRPTW), which has received considerable attention in recent years, using hybrid genetic algorithm. Vehicle Routing Problem with Time Windows is an extension of the well-known Vehicle

A hybrid genetic algorithm for the periodic vehicle routing problem with time windows
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Abstract. We propose a new population-based hybrid meta-heuristic for the periodic vehicle routing problem with time windows. Two neighborhood-based meta-heuristics are used to educate the offspring generated by a new crossover operator to enhance the solution

A hybrid genetic algorithm for sequencing PCB component placement.
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Abstract. A chip shooter machine for electronic components assembly has a movable feeder carrier holding components, a movable XY table carrying a printed circuit board (PCB), and a rotary turret having multiple assembly heads. This paper presents a hybrid genetic

A hybrid genetic algorithm for curriculum based course timetabling
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Abstract. In this paper we describe a genetic algorithm-based approach with two main stages for solving the course timetabling problem. A local search is applied to the algorithm at each stage. The first stage eliminates the violations of hard constraints, and the second

Intrusion detection using rough sets based parallel genetic algorithm hybrid model
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Abstract:Recently machine learning-based Intrusion Detection systems (IDs) have been subjected to extensive researches because they can detect both misuse and anomaly. Most of existing IDs use all features in the network packet to look for known intrusive patterns.

An adaptive fuzzy rule extraction using hybrid model of the fuzzy self-organizing map and thegenetic algorithm with numerical chromosomes
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Abstract In this paper, we propose a hybrid model of the fuzzied Kohonen's Self-Organizing Map and the GA with numerical chromosomes, and automatic fuzzy rule extraction method that uses our model. It is shown that our hybrid model is superior to both of the individual

Protein 3 D HP Model Folding Simulation Using a Hybrid of Genetic Algorithm and Particle Swarm Optimization
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Given the amino-acid sequence of a protein, the prediction of a protein's tertiary structure is known as the protein folding problem. The protein folding problem in the hydrophobic- hydrophilic lattice model is the problem of finding the lowest energy conformation. This is

A grid-based hybrid cellular genetic algorithm for very large scale instances of the CVRP
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ABSTRACT This work presents a hybrid genetic algorithm (GA) for solving the largest existing benchmark instances of the capacitated vehicle routing problem (CVRP). The population of the algorithm is structured by following two classical parallelization models

Optimal placement of PMU and RTU by hybrid genetic algorithm and simulated annealing for multiarea power system state estimation
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Abstract:This paper proposes a hybrid genetic algorithm and simulated annealing (HGS) for solving optimal placement of PMU and RTU for multiarea power system state estimation. Each power system control area includes one PMU and several RTUs. Voltage magnitude

Hybrid optimization of the emission and economic dispatch by the genetic algorithm
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Abstract This paper presents an efficient and reliable technique of optimization with combined economic emission dispatch. This problem has been formulated as a multi- objective problem by considering both economy and emission simultaneously. The bi-

Hybrid real-coded genetic algorithm with quasi-simplex technique
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Summary This paper proposes a new real-value mutation operator and a hybrid real-coded genetic algorithm with quasi-simplex technique using this new mutation operator (RCGAQS). Compared with the classical GA (CGA), RCGAQS has the following

An effective hybrid of hill climbing and genetic algorithm for 2D triangular protein structure prediction
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Abstract Background: Proteins play fundamental and crucial roles in nearly all biological processes, such as, enzymatic catalysis, signaling transduction, DNA and RNA synthesis, and embryonic development. It has been a long-standing goal in molecular biology to

target visitation problem
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ABSTRACT. In this paper we consider the problem of determining an optimal path for an targets. The objective is to minimize the travel distance while maximizing the utility of the visitation order. This is known as the

A hybrid genetic algorithm approach to global low-thrust trajectory optimization
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Curiosity has driven mankind to explore beyond the safe confines of Earth's atmosphere. Probes have been dispatched throughout the solar system to better understand the universe, its laws, and possibly discover extraterrestrial life. These robotic explorers, while

Hybrid genetic algorithm for flexible job-shop scheduling with multi-objective
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Abstract This paper presents a novel algorithm for multi-objective flexible Job-shop scheduling problem based on improved genetic algorithm. The new algorithm adopts non- binary encoding technique and handles the iteration using the dynamic crossover rate

Genetic Algorithm Solution to Optimal Sizing Problem of Small Autonomous Hybrid Power Systems.
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Abstract. The optimal sizing of a small autonomous hybrid power system can be a very challenging task, due to the large number of design settings and the uncertainty in key parameters. This problem belongs to the category of combinatorial optimization, and its

Developed hybrid genetic algorithm for optimizing reverse engineering methods
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Abstract: An important area in Reverse Engineering applications is the combination of multiple scans of a 3D product to model the object. Moreover the registration refinement of multiple range images is a crucial step in multi-view 3D modeling. In the present paper a

Prediction of stock market indices using hybrid genetic algorithm/particle swarm optimization with perturbation term
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Abstract Stock market indices prediction is one of the most important issues in the financial field. Although many prediction models have been developed during the last decade, they suffer a poor performance because indices movement is highly non stationary and volatile

Hybrid Optimization Technique for Circuit Partitioning Using PSO and Genetic Algorithm
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Abstract: In the partitioning main objective is to minimize the number of cuts. For this PSO algorithm is proposed for the optimization of VLSI interconnection (net list) bipartition. Meanwhile, the corresponding evaluation function and the operators of crossover and

A hybrid genetic algorithm for system identification
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Abstract The problem considered is that of approximating an unknown system (plant) by learning the coe cients of a linear model from data collected on the plant performance, using the criterion of minimizing the sum of squared errors between predicted and actual

GEFeWS: A Hybrid Genetic-Based Feature Weighting and Selection Algorithm for Multi-Biometric Recognition.
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Abstract In this paper, we investigate the use of a hybrid genetic feature weighting and selection (GEFeWS) algorithm for multi-biometric recognition. Our results show that GEFeWS is able to achieve higher recognition accuracies than using genetic-based

Genetic algorithm based model predictive control for hybrid systems under a modified mld form
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ABSTRACT: The Mixed Logical Dynamical (MLD) formalism has proved to be an efficient modelling framework for hybrid systems described by dynamics, logic and constraints. Furthermore, it allows formulating and solving practical problems such as control and state

A hybrid feature selection algorithm: Combination of symmetrical uncertainty and geneticalgorithms
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Abstract A hybrid feature selection method called SU-GA-W is proposed to make full use of advantages of filter and wrapper methods. This method falls into two phases. The filter phase removes features with lower SU and guides the initialization of GA population; the

A Hybrid Genetic Algorithm to track the Dutch AEX-index
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Abstract Assuming the market is efficient, an obvious portfolio management strategy is passive where the challenge is to track a certain benchmark, such that equal returns and risks are achieved. In this paper, we investigate an approach for tracking the Dutch AEX-

The discrete time-cost-quality trade-off problem using a novel hybrid genetic algorithm
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Abstract Time, cost and quality are among the major objectives of any project. In recent years, the demands of project stakeholders regarding reductions in the total cost and time of a project along with achieving the desirable quality of the project have risen significantly.

A New Hybrid Genetic Algorithm for Maximum Independent Set Problem.
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1 Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran 2 Department of Computer Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran 3 Department of Mathematical and Computer Science, Yazd University, Yazd,

Transmission loss allocation in deregulated power system using the hybrid genetic algorithm-support vector machine technique
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Abstract:This paper proposes a new method to trace the transmission loss in deregulated power system by incorporating the Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). The idea is to use GA to find the optimal values of hyper-

Estimation of solar cell model parameter by hybrid genetic algorithm using matlab
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Abstract:In the present work, an efficient and accurate approach for the estimation of the solar cell parameters using hybrid genetic algorithm from the given voltage-Current data is proposed. Exact estimation of solar cell data is necessary for getting desired accuracy in

A hybrid Benders/genetic algorithm for vehicle routing and scheduling problem
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This paper presents an optimization model and its application to a classical vehicle routing problem. The proposed model is exploited effectively by the hybrid Benders/genetic algorithm which is based on the solution framework of Benders' decomposition algorithm,

Brain tumor segmentation using hybrid genetic algorithm and artificial neural network fuzzy inference system (anfis)
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ABSTRACT Medical image segmentation plays an important role in treatment planning, identifying tumors, tumor volume, patient follow up and computer guided surgery. There are various techniques for medical image segmentation. This paper presents a image

Improving efficiency in electrical impedance tomography problem by hybrid parallel genetic algorithm and a priori information. In, editor
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Electrical impedance tomography (EIT) consists in determining the electric contrast distribution in the interior of a sensing volume by applying an excitation profile to the external surface and measuring the corresponding response on the same surface. The

Enhanced stutzer index optimization using hybrid genetic algorithm and sequential quadratic programming. J
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Abstract: This study presents a hybrid approach by associating the Genetic Algorithm (GA) and the Sequential Quadratic Programming (SQP) to improve the Stutzer Index optimization. The Stutzer Index is a well-recognized portfolio performance measure that provides

Hybrid genetic algorithm with exact techniques applied to tsp
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Abstract This paper presents the hybridization of the Genetic Algorithm (GA) by using ideas enclosed in exact techniques, like the Branch and Bound (BB), Minimal Spanning Tree and Backtracking Algorithms. It also has been used the Divide and Conquer principle. Two

A new hybrid genetic and simulated annealing algorithm to solve the traveling salesman problem
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Abstract--The Traveling Salesman Problem (TSP) is one of the most widely known non- deterministic polynomial (NP-hard) problems. It is used to check the efficacy of any combinatorial optimization method, and is often used as a testbed. This paper proposes a

Inverse determination of model parameters of nonlinear heat conduction problem using hybrid genetic algorithm
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Abstract: A new interpretation is proposed to solve the inverse heat conduction problem using hybrid genetic algorithm. In order to identify parameters of non-linear heat transfer efficiently and in a robust manner, the hybrid genetic algorithm, which combines genetic Abstract One of the most important phenomena in petroleum industry is the precipitation of heavy organic materials such as asphaltene in oil reservoirs, which can cause diffusivity reduction and wettability alteration in reservoir rock and finally affect oil production and

A hybrid grouping genetic algorithm for examination timetabling
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In this paper, we present an improvement of the Grouping Genetic Algorithm (GGA) which has been described in [6]. The algorithm has been enhanced with local optimisation techniques which are based on problem-specific heuristics and incorporated into the

A self-adaptive hybrid genetic algorithm for optimal groundwater remediation design
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Abstract Groundwater contamination is the result of multiple human activities, such as agriculture, industrial practices and military operations. The traditional remediation approach is to combine pump-and-treat for plume containment and contaminant capture, with other

Optimization of spatial sample configurations using hybrid genetic algorithm and simulated annealing
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Abstract The accuracy of results obtained by geostatistical analysis, regarding spatial prediction, depends substantially on determining more efficient sampling schemes, with a reduced number of samples. This in the sense that the obtained results are similar to the

A multiheuristic approach to resource constrained project scheduling: an adaptive hybrid genetic algorithm
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This chapter describes the resource constrained project scheduling problem (RCPSP), following the assumptions regarding projects, resources, and optimal solutions to the problem. The objective function to the problem is formulated using mathematical terms Abstract In the present paper, a new hybrid method is proposed for grade estimation. In this method, the multilayer perceptron (MLP) network is trained using the combination of the Levenberg–Marquardt (LM) method and genetic algorithm (GA). Having a few samples for

A hybrid modified genetic-nelder mead simplex algorithm for large-scale truss optimization
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ABSTRACT In this paper a hybrid algorithm based on exploration power of the Genetic algorithms and exploitation capability of Nelder Mead simplex is presented for global optimization of multivariable functions. Some modifications are imposed on genetic

A Hybrid Genetic Algorithm For Optimal Hexagonal Tortoise Problem.
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Hexagonal tortoise problem, which was first introduced by an old Korean mathematician suk- Jung Choi (1646-1715)[1], is one of the most complicated tortoise problems. since there has been no general heuristic to solve the hexagonal tortoise, an exhaustive search has been

A hybrid genetic algorithm for solving feeder arrangement and placement sequencing decisions in PCB assembly
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ABSTRACT We consider the operation of a surface mounting technology (SMT) device that mounts various components provided by diverse types of feeders such as cassette, stick, and tray on a printed circuit board (PCB). The problem is to minimize the time needed to

A Hybrid Genetic Algorithm and Particle Swarm Optimization Based Fuzzy Time Series Model TAIFEX and KSE-100 Forecasting
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Abstract:-In this paper we proposed a new evolutionary fuzzy time series forecasting model for Taiwan Futures Exchange (TIAFEX) and Karachi Stock Exchange (KSE-100) forecasting. Our proposed method is based on two-factor high order fuzzy logical relation groups. A

Finding near optimal solutions for vehicle routing problems with time windows using hybrid genetic algorithm
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Abstract The Vehicle Routing Problem with Time Windows (VRPTW) is a well-know and complex combinatorial problem, which has received considerable attention in recent years. This problem has been addressed using many different techniques including both exact

A hybrid genetic algorithm and artificial immune system for informative gene selection
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Summary In this paper, we present a general approach for gene selection of high dimensional DNA Microarray data. The proposed approach represents a powerful new tool in the analysis and exploration of complex data. Very few genes are assumed to anticipate

Multidisciplinary design optimization of a second-generation supersonic transport aircraft using a hybrid genetic/gradient-guided algorithm.
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Summary The purpose of this dissertation is to investigate methods for multivariate and multidisciplinary optimization1 of conceptual aircraft designs, using a secondgeneration

A new multi-objective job shop scheduling with setup times using a hybrid genetic algorithm
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ABSTRACT This paper presents a new multi-objective job shop scheduling with sequence- dependent setup times. The objectives are to minimize the makespan and sum of the earliness and tardiness of jobs in a time window. Scince a job shop scheduling problem

A hybrid of genetic algorithm and particle swarm optimization for antenna design
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Abstract:In this paper, a new effective optimization algorithm called PGHA is presented, which combines in the most effective way the properties of two of the most popular evolutionary optimization approaches now in use for the optimization of electromagnetic

Global optimization based on hybrid clonal selection genetic algorithm for task scheduling
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Abstract Grid computing system is different from conventional distributed computing systems by its focus on large-scale resource sharing and open architecture for services. Resource management and task scheduling is a crucial problem in Grid environments. The aim of

Parameter Optimization of Pitch Controller for Robust Frequency Control in an Isolated Wind-diesel Hybrid Power System Using Genetic Algorithm
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Abstract This paper focuses on the parameter optimization of the pitch controller for robust frequency control in an isolated wind-diesel hybrid power system. The structure of the pitch controller is a practical 1st–order lead-lag compensator. In system modeling, the

Mixed-discrete fuzzy multiobjective optimization of structures using a hybrid genetic algorithm
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Many structural design optimization problems require considering some of the design variables as integer or discrete values. Structural optimization problems involving uncertain and imprecise data can be solved using fuzzy approaches. Many real-life design

Hybrid optimization genetic algorithm (HOGA) with interactive evolution to solve constraint optimization problems for production systems
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Abstract. This article describes the origin and significant associated with the development of the Hybrid Optimization Genetic Algorithms (HOGA) Toolbox with Matlab as they relate to global optimization. HOGA provide three approaches to handle Genetic Algorithms

A Novel Hybrid Artificial Immune System with Genetic Algorithm for Software Cost Estimation
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Abstract: Inaccurate estimation of software projects is of the important and obvious causes of project failures. Studying the related literature we notice that different models have been proposed for Software Cost Estimation (SCE) among which COCOMO model is the most

A hybrid approach for automatic tumor detection of brain MRI using support vector machine and genetic algorithm
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Global Journal of Science, Engineering and Technology (ISSN : 2322-2441) Issue 3, 2012 pp. 1-8 GJSET Publishing, 2012. http://www.gjset.org A Hybrid Approach for Automatic Tumor

A fast hybrid genetic algorithm-Gibbs sampler approach to estimate geoacoustic parameter uncertainties
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Abstract: Genetic algorithm (GA) is a fast algorithm that gives very good maximum a posteriori (MAP) estimates. However, it provides poor estimates for the posterior probability distributions (PPD). On the other hand, an exhaustive search can provide the PPD but will

Blind identification of non-minimum phase FIR systems using higher order statistics andhybrid genetic algorithm
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ABSTRACT In this paper we present a novel method for identification of linear time invariant, non-minimum phase (NMP), FIR systems when only output data are available and the order of system exceeds four. We generally model a non-minimum phase FIR system as an MA Abstract In this paper we draw on two stochastic optimization techniques, Simulated Annealing and Genetic Algorithm (SAGA), to create a hybrid to determine the optimal design of nonlinear Simulated Moving Bed (SMB) systems. A mathematical programming model

A hybrid genetic algorithm for integrated project task and multi-skilled workforce scheduling
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Abstract This paper deals with the project-scheduling and staff-allocation problem, in which each multi-skilled human resource is capable to perform multiple tasks and has various regular and overtime salary cost, and the project is operated with daily overhead. The objective of the scheduling soft real-time tasks is to minimize total tardiness and the scheduling these tasks on multiprocessor system is NP-hard problem. In this chapter, scheduling algorithms for soft real-time tasks using genetic algorithm (GA) are introduced.

The Application of a Hybrid Artificial Neural Network and Genetic Algorithm (ANN-GA) to Mapping of Wind Speed Profile for Electrical Energy applications: A
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ABSTRACT Since wind speed greatly influences the issues such as the scheduling of a power system, and the dynamic control of the wind turbine, wind speed prediction is critical for wind energy conversion systems. In this study, a Hybrid Artificial Neural Network and

A hybrid artificial immune genetic algorithm with fuzzy rules for breast cancer diagnosis
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ABSTRACT The automatic diagnosis of breast cancer is an important, real-world medical problem. In this paper we give an introduction to fuzzy systems, genetic algorithms and artificial immune system, and then we introduce a hybrid algorithm that gathers the genetic

Using hybrid genetic and Nelder-Mead algorithm for decoupling of MIMO systems with application on two coupled distillation columns process
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Abstract:Multiple Input Multiple Output (MIMO) systems are characterized by significant interactions (ie: coupling) between their inputs and their different outputs. The control of MIMO systems is usually implemented using sets of Single Input Single Output (SISO)

HPSOM: a hybrid particle swarm optimization algorithm with genetic mutation
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Abstract. In this paper, a hybrid particle swarm optimization algorithm (HPSOM) that uses the mutation process to improve the standard particle swarm optimization (PSO) algorithm is presented. The main idea of the HPSOM is to integrate the PSO with genetic algorithm

A hybrid optimization algorithm based on genetic algorithm and ant colony optimization
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ABSTRACT In optimization problem, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have been known as good alternative techniques. GA is designed by adopting the natural evolution process, while ACO is inspired by the foraging behaviour of

A comparison between the hybrid using genetic algorithm and the pure hybridwatermarking scheme
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Abstract:The comparison between the hybrid watermarking using genetic algorithm and the pure hybrid DCT-SVD (Discrete Cosine Transform-Singular Value Decomposition) is presented. The watermark scheme is based on DCT-SVD]; applying DCT to the host

A Hybrid memetic algorithm (Genetic alsorithm and Great Delugu Local search) with Back-propagation classifier for Fish Recognition
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Abstract The aim of this study is to establish a hybrid method to optimize the performance of back-propagation classifier for fish classification by using Memetic Algorithm (MA)(genetic algorithm and great deluge local search). This is to be performed by utilizing the ability of

Hybrid of genetic algorithm and great deluge algorithm for rough set attribute reduction
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Abstract: The attribute reduction problem is the process of reducing unimportant attributes from a decision system to decrease the difficulty of data mining or knowledge discovery tasks. Many algorithms have been used to optimize this problem in rough set theory. The

Artificial neural network with hybrid Taguchi-genetic algorithm for nonlinear MIMO model of machining processes
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Abstract. This paper developed an artificial neural network (ANN) model with hybrid Taguchi- genetic algorithm (HTGA) for the nonlinear multiple-input multiple-output (MIMO) model of machining processes. The HTGA in the MIMO ANN model finds the optimal parameters (ie

A Hybrid Genetic Algorithm Approach to a Departmental Class Timetabling Problem Using Efficient Data Structures
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ABSTRACT The application of Genetic Algorithm with a local search operation performed within its loop has provided very accurate results, but the algorithm take a lot of time to arrive at an optimal solution. This paper describes the use of a Hybrid Genetic Algorithm using

Hybrid modeling and optimization of hardness of surface produced by electric discharge machining using artificial neural networks and genetic algorithm
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ABSTRACT The present work is aimed at optimizing the hardness of surface produced in die sinking electric discharge machining (EDM) by considering the simultaneous affect of various input parameters. The experiments are carried out on Ti6Al4V, HE15, 15CDV6

Solving protein folding problem using hybrid genetic clonal selection algorithm
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Abstract: Alzheimer's disease, Cystic fibrosis, Mad Cow disease, an inherited form of emphysema, even many cancers. Recent discoveries show that all these apparently unrelated diseases result from protein folding gone wrong. As though that weren't enough,

Decentralized sliding mode controller based on genetic algorithm and a hybrid approach for interconnected uncertain non linear systems
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Abstract A new type controller, recurrent fuzzy neural networks-fuzzy-sliding mode controller (FRNN-FSMC), is developed for a class of large-scale systems with unknown bounds of highorder interconnections and disturbances. The main purpose is to eliminate the

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Hybrid Approach of Genetic Algorithm in Case of Planning a Cellular Manufacturing System
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Abstract: One important issue regarding the implementation of cellular manufacturing systems relates to deciding whether to convert an existing job shop into a cellular manufacturing system comprehensively in a single go, or in stages by forming cells one


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