Quantitative analysis and performance study of ant colony optimization models applied to multi-mode resource constraint project scheduling problems

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URI: https://hdl.handle.net/11556/2202
ISSN: 2194-5357
ISBN: 9789811037276
DOI: 10.1007/978-981-10-3728-3_15
Publication date
2017
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Springer Verlag
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Abstract
Constraint Satisfaction Problems (CSP) belongs to this kind of traditional NP-hard problems with a high impact in both, research and industrial domains. However, due to the complexity that CSP problems exhibit, researchers are forced to use heuristic algorithms for solving the problems in a reasonable time. One of the most famous heuristic algorithms is Ant Colony Optimization (ACO) algorithm. The possible utilization of ACO algorithms to solve CSP problems requires the design of a decision graph where the ACO is executed. Nevertheless, the classical approaches build a graph where the nodes represent the variable/value pairs and the edges connect those nodes whose variables are different. In order to solve this problem, a novel ACO model have been recently designed. The goal of this paper is to analyze the performance of this novelty algorithm when solving Multi-Mode Resource-Constraint Satisfaction Problems. Experimental results reveals that the new ACO model provides competitive results whereas the number of pheromones created in the system is drastically reduced.
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Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2017.
Keywords
Ant colony optimization , Oblivion rate , Pheromone control , Resource-Constraint project scheduling problems , Control and Systems Engineering , General Computer Science
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Gonzalez-Pardo , A , Del Ser , J & Camacho , D 2017 , Quantitative analysis and performance study of ant colony optimization models applied to multi-mode resource constraint project scheduling problems . in J Del Ser (ed.) , Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) . Advances in Intelligent Systems and Computing , vol. 514 , Springer Verlag , pp. 145-154 , Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 , Bilbao , Spain , 22/02/17 . https://doi.org/10.1007/978-981-10-3728-3_15
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