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International Conference on Harmony Search Algorithm

ICHSA 2017: Harmony Search Algorithm pp 145–154Cite as

Quantitative Analysis and Performance Study of Ant Colony Optimization Models Applied to Multi-mode Resource Constraint Project Scheduling Problems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 514))

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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Acknowledgements

This work has been supported by the research projects: EphemeCH (TIN2014-56494-C4-4-P) Spanish Ministry of Economy and Competitivity, CIBERDINE S2013/ICE-3095, both under the European Regional De-velopment Fund FEDER, Airbus Defence&Space (FUAM-076914 and FUAM-076915), BID3ABI (Basque Government), and RiskTrack (JUST-2015-JCOO-AG-723180). Javier Del Ser is also grateful to the Basque Government for its support through the BID3ABI project.

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Authors and Affiliations

  1. Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain

    Antonio Gonzalez-Pardo & David Camacho

  2. TECNALIA, 48160, Derio, Spain

    Javier Del Ser

  3. University of Basque Country EHU/UPV, 48009, Bilbao, Bizkaia, Spain

    Javier Del Ser

  4. Basque Center for Applied Mathematics, 48009, Bilbao, Bizkaia, Spain

    Javier Del Ser

Authors
  1. Antonio Gonzalez-Pardo
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  2. Javier Del Ser
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  3. David Camacho
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Corresponding author

Correspondence to Antonio Gonzalez-Pardo .

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Editors and Affiliations

  1. TECNALIA, University of the Basque Country ‎(UPV/EHU), Basque Center for Applied Mathematics (BCAM‎), Bilbao, Spain

    Javier Del Ser

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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: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_15

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  • DOI: https://doi.org/10.1007/978-981-10-3728-3_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3727-6

  • Online ISBN: 978-981-10-3728-3

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