A Simulated Annealing Algorithm Approach for Supermarket Location Problem

In modern production systems, the ever-increasing product variety is a major challenge for the in-house logistics systems used to feed mixed-model assembly lines with the necessary components. In response to this problem, many manufacturers from the automobile industry have adopted supermarket concept to provide flexible and reliable part feeding. In this context, supermarket is a decentralized logistics center where the parts are stored close to the assembly line and transported to the stations via small tow trains. Within the scope of this study, the problem of determining the number and location of supermarkets to be established on the operational floor has been discussed. In previous studies, methods such as dynamic programming and genetic algorithm have been used to solve the problem. Considering that neighboring algorithms can be effective in solving the problem, an annealing simulation algorithm was developed in our study and the algorithm was tested on a number of test problems. As a result of the tests, it was found that the developed algorithm gave successful results in low running times