Population size, search space and quality of solution: an experimental study

Evolutionary algorithms (EAs) has attracted increasing attention in recent years, as powerfully computational technique, 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 algorithm. In this paper, we investigate the effect of population sizes on the quality of solutions to be obtained, the computational time required and the size of search spaces of the problems under consideration. We select a two-stage transportation problem as a test case and also use a well known conventional optimization technique to compare the solutions. The numerical results are analyzed and the interesting findings are discussed.