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Evolving Ant Colony Optimization
Advances in Complex Systems, 1998Ant Colony Optimization (ACO) is a promising new approach to combinatorial optimization. Here ACO is applied to the traveling salesman problem (TSP). Using a genetic algorithm (GA) to find the best set of parameters, we demonstrate the good performance of ACO in finding good solutions to the TSP.
Hozefa M. Botee, Eric Bonabeau
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Ant Colony Optimization for Configuration
2008 20th IEEE International Conference on Tools with Artificial Intelligence, 2008An inherent difficulty in enumerative search algorithms for optimisation is the combinatorial explosion that occurs when increasing the size of the input. Among incomplete algorithms that address this issue, ant colony optimization(ACO) uses a combination of random and heuristic methods plus reinforcement learning, which proved efficient on a wide ...
Patrick Albert +2 more
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Classification With Ant Colony Optimization
IEEE Transactions on Evolutionary Computation, 2007Ant colony optimization (ACO) can be applied to the data mining field to extract rule-based classifiers. The aim of this paper is twofold. On the one hand, we provide an overview of previous ant-based approaches to the classification task and compare them with state-of-the-art classification techniques, such as C4.5, RIPPER, and support vector machines
David Martens +5 more
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Deception in Ant Colony Optimization
2004The search process of a metaheuristic is sometimes misled. This may be caused by features of the tackled problem instance, by features of the algorithm, or by the chosen solution representation. In the field of evolutionary computation, the first case is called deception and the second case is referred to as bias.
Blum, Christian, Dorigo, Marco
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Ant Colony Optimization: An Overview
2002Ant Colony Optimization (ACO) is a class of constructive meta-heuristic algorithms sharing the common approach of constructing a solution on the basis of information provided both by a standard constructive heuristic and by previously constructed solutions. This tutorial is composed of three parts.
Maniezzo V., Carbonaro A.
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Modeling the Dynamics of Ant Colony Optimization
Evolutionary Computation, 2002The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants ...
Daniel Merkle, Martin Middendorf
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Applied Mathematics and Computation, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lídice Camps Echevarría +4 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lídice Camps Echevarría +4 more
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Ant Colony Optimization with Castes
2008Ant Colony Optimization (ACO) is a nature inspired metaheuristic for solving optimization problems. We present a new general approach for improving ACO adaptivity to problems, Ant Colony Optimization with Castes (ACO+C). By using groups of ants with different characteristics, known as castes in nature, we can achieve better results and faster ...
Oleg Kovárík, Miroslav Skrbek
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Ant Colony Optimization on a Budget of 1000
2014Ant Colony Optimization (ACO) was originally developed as an algorithmic technique for tackling NP-hard combinatorial optimization problems. Most of the research on ACO has focused on algorithmic variants that obtain high-quality solutions when computation time allows the evaluation of a very large number of candidate solutions, often in the order of ...
Perez Caceres, Leslie +2 more
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2018
The ant colony optimization (ACO) technique is a vital part of swarm intelligence based on the social instincts of the real ants toward their community that helps them to collectively work together to achieve a common goal. These tiny insects have inspired numerous methods and techniques out of which the most sought after and successful is the general ...
Bandana Mahapatra, Srikanta Patnaik
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The ant colony optimization (ACO) technique is a vital part of swarm intelligence based on the social instincts of the real ants toward their community that helps them to collectively work together to achieve a common goal. These tiny insects have inspired numerous methods and techniques out of which the most sought after and successful is the general ...
Bandana Mahapatra, Srikanta Patnaik
openaire +1 more source