Extended hybrid tabu search and simulated annealing algorithm for location-inventory model with multiple products, multiple distribution centers and multiple capacity levels

Abstract

In this paper, a single objective model is proposed for the location-inventory problem, which considers multiple products, multiple distribution centers (DCs) and multiple capacity levels. In the proposed model, the number of assigned customers to each DC and the number of opened DCs is limited. The main objective of the model is selecting a set of DCs to serve customers and assigning customers to the opened DC in order to minimize the total expected costs of locating DCs, shipment, transportation and inventory costs. The main objective of this paper is to propose a novel and efficient combination of Tabu search (TS) and simulated annealing (SA) methods for solving the proposed mathematical model. For this purpose, the Tabu list of TS method is aggregated with the neighborhood structure of the SA method to improve the speed of convergence. For validation of the introduced solution method, we compared its performance against Lingo software and classical SA and TS methods. The experimentation is performed using 48 test problems in small, medium, and large sizes and the results are compared with the LINGO 8.0 results for the same problems. The results indicate that the proposed algorithm is effective and efficient for a wide variety of problem sizes. Also, the computational time of the SA-TA algorithms shows how fast this algorithm could find an optimal solution within a short computational time.