TS and ACO in Hybrid Approach for Product Distribution Problem

Karim Bouamrane, Khadidja Yachba, Belayachi Naima

OAI: oai:igi-global.com:298678 • DOI: 10.4018/JGIM.298678

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.

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