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TS and ACO in Hybrid Approach for Product Distribution Problem

TS and ACO in Hybrid Approach for Product Distribution Problem

Khadidja Yachba, Belayachi Naima, Karim Bouamrane
Copyright: © 2022 |Volume: 30 |Issue: 8 |Pages: 17
ISSN: 1062-7375|EISSN: 1533-7995|EISBN13: 9781668435717|DOI: 10.4018/JGIM.298678
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MLA

Yachba, Khadidja, et al. "TS and ACO in Hybrid Approach for Product Distribution Problem." JGIM vol.30, no.8 2022: pp.1-17. http://doi.org/10.4018/JGIM.298678

APA

Yachba, K., Naima, B., & Bouamrane, K. (2022). TS and ACO in Hybrid Approach for Product Distribution Problem. Journal of Global Information Management (JGIM), 30(8), 1-17. http://doi.org/10.4018/JGIM.298678

Chicago

Yachba, Khadidja, Belayachi Naima, and Karim Bouamrane. "TS and ACO in Hybrid Approach for Product Distribution Problem," Journal of Global Information Management (JGIM) 30, no.8: 1-17. http://doi.org/10.4018/JGIM.298678

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Abstract

In order to solve the transport problem, a set of bio-inspired meta heuristics are proposed, they are based on the natural behavior of swarms, bees, birds, and ants that had emerged as an alternative to overcome the difficulties presented by conventional methods in the field of optimization. In this work, the authors use a hybrid of two optimization methods in order to solve the problem of product distribution from a central warehouse to the different warehouses distributed in different cities. The optimization of the distribution process is done by identifying through the proposed contribution the optimal path that combines between a minimum distance with a good condition of the path taken. In order to situate the approach proposed in this article, the authors compare the results obtained with the result obtained using ACO without hybridization, the results obtained by hybridizing the two methods Ant Colony Optimization (ACO) and Tabu Search (TS) are better.