Parallel Optimization Algorithm for Competitive Facility Location

Abstract

A stochastic search optimization algorithm is developed and applied to solve a bi-objective competitive facility location problem for firm expansion. Parallel versions of the developed algorithm for shared- and distributed-memory parallel computing systems are proposed and experimentally investigated by approximating the Pareto front of the competitive facility location problem of different scope. It is shown that the developed algorithm has advantages against its precursor in the sense of the precision of approximation. It is also shown that the proposed parallel versions of the algorithm have almost linear speed-up when solving competitive facility location problems of different scope reasonable for practical applications.