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An Ant Algorithm with a New Pheromone Evaluation Rule for Total Tardiness Problems
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Anti-pheromone as a Tool for Better Exploration of Search Space
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CSR'06 Proceedings of the First international computer science conference on Theory and Applications
Solving a bi-objective flowshop scheduling problem by pareto-ant colony optimization
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Analog Integrated Circuits and Signal Processing
Computers & Mathematics with Applications
Filter-based optimization techniques for selection of feature subsets in ensemble systems
Expert Systems with Applications: An International Journal
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In this paper we propose a new approach to solve bi-criterion optimization problems with ant algorithms where several colonies of ants cooperate in finding good solutions. We introduce two methods for co-operation between the colonies and compare them with a multistart ant algorithm that corresponds to the case of no cooperation. Heterogeneous colonies are used in the algorithm, i.e. the ants differ in their preferences between the two criteria. Every colony uses two pheromone matrices -- each suitable for one optimization criterion. As a test problem we use the Single Machine Total Tardiness problem with changeover costs.