Abstract
In this paper, a generalized variant of the multi facility Weber problem is proposed, where each customer must be satisfied by a single capacitated facility. To solve the problem, the allocation phase of the alternate location–allocation (ALA) is strengthened by a priority-based approach. Computational experiments are implemented on a set of random test instances, along with a set of instances taken from the literature. Computational results compared with GAMS/BARON indicate that the priority-based ALA solves large-scale instances within promising computational time and outperforms GAMS/BARON in terms of solution quality. This success rate is achieved in nearly 80 % of studied cases. Finally, some guidelines for future research are presented.
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