SOLVING A NEW PRIORITY M/M/C QUEUE MODEL FOR A MULTI- MODE HUB COVERING LOCATION PROBLEM BY MULTI- OBJECTIVE PARALLEL SIMULATED ANNEALING

In this paper, a new priority M/M/c queuing hub covering problem is presented, in which products with high priority are selected for service ahead of those with low priority. In addition, a mixed-integer nonlinear mathematical programming model is presented to find a good solution of the given problem. Due to its computational complexity, we propose a multi-objective parallel simulated annealing (MOPSA) algorithm and a new solution representation is developed to solve a number of instances. Furthermore, some computational experiments are provided to illustrate the efficiency of the presented model and proposed MOPSA. In order to show the higher performance of the proposed MOPSA, two well-known evolutionary algorithms, namely a non-dominated sorting genetic algorithm (NSGA-II) and Pareto Archive Evolution Strategy (PAES), are considered and the related results are compared and analyzed. Finally, the conclusion is presented.

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