Solving capacitated p-median problem using genetic algorithm

Capacitated p-median problem (CPMP) is an important variation of facility location problem in which p capacitated medians are economically selected to serve a set of demand vertices so that the total assigned demand to each of the candidate medians must not exceed its capacity. This paper presents a genetic algorithm to solve the CPMP. Two different assignment techniques namely, classical assignment method and assignment through urgencies are used to assign the demand points to the p selected medians. The behavior and efficiency of the assignment scenarios are examined and compared on CPMP. According to the results, the classical scenario shows superiority in time consuming, whereas the assignment through urgencies scenario is absolutely superior in quality of the obtained solutions over the classical one. In order to check for quality and validity of the suggestive method, we compare the final solution produced over the 10 test problems of Osman and Christofides. Comparison of the results indicates good quality and solutions.