Parallel Genetic Algorithm for Capacitated P-median Problem

This paper presents an implementation of a specific genetic algorithm on a high performance computing cluster. The algorithm is designed to approximately solve the capacitated p-median problem. Since the p-median problem has been proven to be NP-hard, exact algorithms are not efficient in solving it in reasonable time. Therefore it is helpful to use metaheuristics like genetic algorithm. In an endeavor to obtain the best solution, even for large instances, we look for best ways how to use all computing power that is in our disposal. The obvious method to achieve that is to design parallel algorithm and let it run on a high performance computing cluster.