RESEARCH PAPERS

ant colony Optimization




Ant colony optimization: overview and recent advances
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Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic solution construction procedures that build candidate solutions for the problem instance 

Ant Colony Optimization
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Page 1. Ant Colony Optimization Nuno Abreu Muhammad Ajmal Zafeiris Kokkinogenis Behdad Bozorg FEUP-DEEC  2005 Dorigo M., Stutzle T., Ant Colony Optimization, Ant Colony Optimization, MIT Press 2004 Page 18. AntPacking – An Ant Colony Optimization Approach for 

Ant Colony Optimization
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Figure: Percentage of ants per 3-min period passing on the two branches of the bridge (inset). Colony of 1000 workers. (Deneubourg et al. [1990])  Figure: An ant colony selecting the short branches on both modules of the bridge; (a) one module of the bridge, (b) and 

Ant Colony Optimization based on multi-searching to estimate the natural gas demand: Case of Turkey
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In this paper we propose a new version of the Ant Colony Optimization (ACO) to predict the natural gas demand problem. This heuristic approach will estimate the Turkey's natural gas demand based on economic indicators. The well-known ACO is multi-agent systems in 

Ant Colony Optimization
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4l aprile 2012 siano quelli immessi direttamente all'interno del codice. In alternativa si possono inserire tali dati tramite terminale, decommentando la parte di codice relativa alla lettura dei dati da file gi implementata nel software. Nel caso in cui si volesse analizzare 

A Collaborative Combination between Column Generation and Ant Colony Optimization for Solving Set Packing Problems
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ABSTRACT The Set Packing Problem (SPP) is a well-known NP-hard combinatorial optimization problem. This paper addresses the SPP through a practical case study, namely the Railway Infrastructure Capacity (RIC) problem. SPP instance sizes yielded by this 

Image edge detection using ant colony optimization
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ABSTRACT Ant colony optimization (ACO) is a population-based metaheuristic that mimics the foraging behavior of ants to find approximate solutions to difficult optimization problems. It can be used to find good solutions to combinatorial optimization problems that can be 

Optimal use of expert knowledge in ant colony optimization for the analysis of epistasis in human disease
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The availability of chip-based technology has transformed human genetics and made routine the measurement of thousands of DNA sequence variations giving rise to an informatics challenge. This challenge is the identification of combinations of interacting 

Solving the post enrolment course timetabling problem by ant colony optimization
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ABSTRACT In this work we present a new approach to tackle the problem of Post Enrolment Course Timetabling as specified for the International Timetabling Competition 2007 (ITC2007), competition track 2. The heuristic procedure is based on Ant Colony 

Two novel ant colony optimization approaches for Bayesian network structure learning
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ABSTRACT Learning Bayesian networks from data is an NP hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational complexity of this task. Difficult challenges remain however in reducing 

Digital watermarking using ant colony optimization in fractional Fourier domain
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ABSTRACT The paper describes the implementation of a watermarking embedding and retrieval technique using a conceptual approach of bio-inspired algorithm eg ant colony optimization (ACO). The essential construct of ACO is pheromone; hence the detection 

Estimation-based ant colony optimization and local search for the probabilistic traveling salesman problem
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ABSTRACT The use of ant colony optimization for solving stochastic optimization problems has received a significant amount of attention in recent years. In this paper, we present a study of enhanced ant colony optimization algorithms for tackling a stochastic optimization 

Beam Orientation Optimization Using Ant Colony Optimization in Intensity Modulated Radiation Therapy
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ABSTRACT In intensity modulated radiation therapy (IMRT) treatment planning, beam angles are usually preselected on the basis of experience and intuition. Therefore, getting an appropriate beam configuration needs a very long time. Based on the present situation, 

Variable neighborhood search and ant colony optimization for the rooted delay-constrained minimum spanning tree problem
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The rooted delay-constrained minimum spanning tree problem is an NP-hard combinatorial optimization problem arising for example in the design of centralized broadcasting networks where quality of service constraints are of concern. We present two new approaches to 

Swarm intelligence inspired multicast routing: an ant colony optimization approach
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ABSTRACT The advancement of network induces great demands on a series of applications such as the multicast routing. This paper firstly makes a brief review on the algorithms in solving routing problems. Then it proposes a novel algorithm called the distance complete 

Memory-based immigrants for ant colony optimization in changing environments
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Ant colony optimization (ACO) algorithms have proved that they can adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity. DOPs are important due to their similarities to many real-world applications. Several approaches 

An analysis of algorithmic components for multiobjective ant colony optimization: A case study on the biobjective TSP
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In many practical problems, several conflicting criteria exist for evaluating solutions. In recent years, strong research efforts have been made to develop efficient algorithmic techniques for tackling such multi-objective optimization problems. Many of these algorithms are 

Reverse Game Theory Approach for Aggregator Nodes Selection with Ant Colony Optimization Based Routing in Wireless Sensor Network
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ABSTRACT The self–configurable, randomly distributed, adhoc technology based wireless sensor networks can be invaluable in various domestic and military applications for collecting, processing and propagating wide range of complex environmental data. 

Ant colony optimization with immigrants schemes in dynamic environments
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In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been developed for EAs to increase the diversity of the population and enhance the 

A Comparison of Evolutionary Algorithms and Ant Colony Optimization for Interactive Software Design
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ABSTRACT Evolutionary algorithms have a well-documented history of success in Search- Based Software Engineering, but arguably the preponderance of evolutionary algorithms stems from history rather than as a conscious design choice of meta-heuristic based on 

Elitist continuous ant colony optimization algorithm for optimal management of coastal aquifers
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ABSTRACT This paper presents an evolutionary based approach to achieve optimal management of a coastal aquifer to control saltwater intrusion. An improved Elitist Continuous Ant Colony Optimization (ECACO) algorithm is employed for optimal control 

A survey paper on Ant Colony Optimization Routing algorithm for selecting Multiple Feasible Paths for Packet Switched Networks
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ABSTRACT ACO algorithms for datagram networks was given by Di CaroDorigo, in year 1996. Basic mechanisms in typical ACO routing algorithms is Ant-like agents are proactively generated at the nodes to find/check paths toward assigned destinations Ants move hop- 

Strong combination of ant colony optimization with constraint programming optimization
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ABSTRACT We introduce an approach which combines ACO (Ant Colony Optimization) and IBM ILOG CP Optimizer for solving COPs (Combinatorial Optimization Problems). The problem is modeled using the CP Optimizer modeling API. Then, it is solved in a generic 

A critical analysis of parameter adaptation in ant colony optimization
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ABSTRACT Applying parameter adaptation means operating on parameters of an algorithm while it is tackling an instance. For ant colony optimization, several parameter adaptation methods have been proposed. In the literature, these methods have been shown to 

Learning bayesian network equivalence classes with ant colony optimization
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ABSTRACT Bayesian networks are a useful tool in the representation of uncertain knowledge. This paper proposes a new algorithm called ACO-E, to learn the structure of a Bayesian network. It does this by conducting a search through the space of equivalence classes of 

A parallel ant colony optimization algorithm based on fine-grained model with GPU-acceleration
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ABSTRACT Fine-grained parallel ant colony optimization algorithm (FGACO), though a popular and robust strategy for solving complicated optimization problems, is sometimes inconvenient to use as its population size is restricted by heavy data communication and 

Ant colony optimization for air traffic conflict resolution
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 Ant Colony Optimization for Air Traffic Conflict Resolution Nicolas Durand, Jean-Marc

Efficient Power Scheduling via Stability Index Based Tracing Technique and Blended Crossover Continuous Ant Colony Optimization
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ABSTRACT This paper proposes a new method for performing power scheduling via power tracing based generator selection method considering voltage stability improvement and cost reduction. Unlike the previous power tracing methods that performed the selection of 

A hybrid system for facility layout by integrating simulation and ant colony optimization
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ABSTRACT In this paper, we integrated simulation and ant colony optimization for solving the facility layout problems in public service building. The optimization goal was to minimize the pedestrians' walking time between facilities in the building. By means of VISSIM, a 

An ant colony optimization approach to multi-objective optimal design of symmetric hybrid laminates for maximum fundamental frequency and minimum cost
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ABSTRACT An ant colony optimization algorithm for optimum design of symmetric hybrid laminates is described. The objective is simultaneous maximization of fundamental frequency and minimization of cost. Number of surface and core layers made of high- 

An incremental ant colony algorithm with local search for continuous optimization
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April 2011ABSTRACT ACOR is one of the most popular ant colony optimization algorithms for tackling continuous optimization problems. In this paper, we pro- pose IACOR-LS, which is a variant of ACOR that uses local search and that features a growing solution archive. 

Object-Guided Ant Colony Optimization Algorithm with Enhanced Memory for Traveling Salesman Problem
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ABSTRACT In this study, we presents an object-guided ACO algorithm which is consisted of ants with enhanced memory. In the process of solution construction, each ant stores a complete solution in its enhanced memory. Each time ant selects a solution component 

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 construction  xxxx Keywords: Knowledge-based expert systems Ant colony optimization Genetic algorithms Fuzzy logic Energy demand forecastingABSTRACT

Partitioning of mobile network into location areas using ant colony optimization
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ABSTRACT Location determination of users in a cellular mobile network is an important issue in the area of location management. One strategy used in location management is to partition the network into location areas, in such a way that the total cost is a minimum. 

Critical Path Method in a Project Network using Ant Colony Optimization
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ABSTRACT Critical Path Method (CPM) is useful for planning, analyzing, controlling the progress and the completion of large and complex projects. The ant colony optimization (ACO) algorithms are applied to solve many complex combinatorial optimization problems 

Self-evolving ant colony optimization and its application to traveling salesman problem
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ABSTRACT Ant colony optimization (ACO) algorithms are a recently developed, population- based approach which has been successfully applied to combinatorial optimization problems. However, in the ACO algorithms, it is difficult to adjust the balance between 

On the Evaporation Mechanism in the Ant Colony Optimization Algorithms
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ABSTRACT Ant colony optimization is an evolutionary algorithm in which ant colonies assist in locating shortest routes to food sources. One of the factors influencing the ant's behavior and performance is the pheromone evaporation. In this paper, a new approach towards 

Optimal Parameter Identification in Ant Colony Optimization for Load Balancing in Grid Computing
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ABSTRACT Ant colony optimization (ACO) is a Swarm Intelligence technique which inspired from the foraging behaviour of real ant colonies. The ants deposit pheromone on the ground in order to mark the route for identification of their routes from the nest to food that should 

Implementing Ant Colony Optimization for Test Case Selection and Prioritization
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ABSTRACT Regression Testing is an inevitable and a very costly activity to be performed, often in a time and resource constrained environment. Thus we use techniques like Test Case Selection and Prioritization, to select and prioritize a subset from the complete test 

Solving a unique shortest path problem using Ant Colony Optimization
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ABSTRACT Ant Colony Optimisation (ACO) has in the past proved suitable to solve many optimisation problems. This research explores the ability of the ACO algorithm to balance two quality metrics (length and cost) in its decision making process. Results are given for a 

A hybrid CDMA multiuser detector with ant colony optimization and code filtering system
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ABSTRACT In this study, a hybrid approach with Ant Colony Optimization (ACO) and Code Filtering System (CFS) is proposed for DS-CDMA multiuser detection. In CFS, the method of Lagrange multipliers is applied to set the threshold in order to make the judgment of the 

Ant-CSP: An ant colony optimization algorithm for the closest string problem
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ABSTRACT Algorithms for sequence analysis are of central importance in computational molecular biology and coding theory. A very interesting problem in this field is the Closest String Problem (CSP) which consists in finding a string t with minimum Hamming distance 

Ant Colony Optimization Routing Algorithm with Tabu Search
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ABSTRACT The route search problem is applied to various engineering fields. Many researchers study this problem. In this paper, we propose a new hybrid routing algorithm which combines Tabu search with Ant Colony Optimization. The proposed hybrid 

Ant colony optimization applied to network schematization
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This paper details an on-going PhD project that is studying the application of Ant Colony Optimization (ACO) to automated map generalization problems. One objective of the project is to compare ACO with alternative approaches. The paper begins by introducing the 

A cooperative network game efficiently solved via an ant colony optimization approach
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In this paper, a Cooperative Network Game (CNG) is introduced. In this game, all players have the same goal: display a video content in real time, with no cuts and low buffering time. Inspired in cooperation and symmetry, all players should apply the same strategy, 

Ant Colony Optimization approach for Solving FPGA routing with minimum Channel Width
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ABSTRACT In this paper ANT colony optimization algorithm has been proposed to solve FPGA routing in FPGA design architecture with minimum umbers of tracks per channel. In our method geometric FPGA routing task is transformed into a Boolean satisfiability (SAT) 

Solving the minimum label spanning tree problem by ant colony optimization
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Autonomous units for solving the traveling salesperson problem based on ant colony optimization
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Communities of autonomous units are rule-based and graph-transformational systems with a well-defined formal semantics. The autonomous units of a community act and interact in a common environment while striving for their goals. Ant colony systems consist of a set of 

MANET routing protocols based on Ant Colony Optimization
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ABSTRACT Apart from tremendous research being done all around the globe, still ad hoc networks are a big challenge for the researchers. Routing in an ad hoc network is extremely challenging because of its dynamic nature, limited bandwidth and power energy. 

Ant colony optimization for traffic dispersion routing
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ABSTRACT Ant Colony Optimization (ACO) has proven to be a very powerful optimization heuristic for combinatorial optimization problems. This paper introduces a new type of ACO algorithm that will be used for routing along multiple routes in a network as opposed to 


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