Solving multi-objective fixed charged transportation problem using a modified particle swarm optimization algorithm

Abstract

Particle Swarm Optimization (PSO) is population-based algorithm established and enhanced to solve a wide variety of real-life problems. During the last decade, different aspects of PSO have been modified and many variants have been proposed. In this paper, a modified PSO is proposed to solve multi-objective fixed charge transportation problem wherein it optimizes the transportation cost (variable and fixed) as well as time to deliver goods from sources to destinations satisfying certain constraints. The method starts with the variable cost only and then with addition of fixed cost, iterates toward optimal Pareto pair. The simulation results show a significant performance gain by the proposed method and prove it as a competent alternative to existing methods.