The capacitated multi-facility location–allocation problem with probabilistic customer location and demand: two hybrid meta-heuristic algorithms

A new mathematical model for the capacitated multi-facility location–allocation problem with probabilistic customers' locations and demands is developed in this article. The model is formulated into the frameworks of the expected value model (EVM) and the chance-constrained programming (CCP) based on two different distance measures. In order to solve the model, two hybrid intelligent algorithms are proposed, where the simplex algorithm and stochastic simulation are the bases for both algorithms. However, in the first algorithm, named SSGA, a special type of genetic algorithm is combined and in the second, SSVDO, a vibration-damping optimisation (VDO) algorithm is united. The Taguchi method is employed to tune the parameters of the two proposed algorithms. Finally, some numerical examples are given to illustrate the applications of the proposed methodologies and to compare their performances.

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