Solving Transshipment Problem using EAs: How Good are the Solutions?

Abstract

Evolutionary Algorithms have attracted increasing attention in recent years, as powerful computational techniques, for solving many complex real-world problems. The successful application of Evolutionary algorithms to optimization problems is dependent on the methods and parameters used for the algorithms. In this paper, we develop three evolutionary algorithms for solving a transshipment problem. We investigate the effect of population sizes on the quality of solutions to be obtained, the computational time to be required and the size of search spaces of the problems under consideration. We also use a well-known conventional optimization package to compare the quality of solutions. The numerical results are analyzed and the interesting findings are discussed.