MULTIOBJECTIVE GENETIC ALGORITHM AND ITS APPLICATIONS TO FLOWSHOP SCHEDULING

In this paper, we propose a multi-objective genetic algorithm and appl y it to flowshop scheduling. The characteristic features of our algori thm are its selection procedure and elite preserve strategy. The selec tion procedure in our multi-objective genetic algorithm selects indivi duals for a crossover operation based on a weighted sum of multiple ob jective functions with variable weights. The elite preserve strategy i n our algorithm uses multiple elite solutions instead of a single elit e solution. That is, a certain number of individuals are selected from a tentative set of Pareto optimal solutions and inherited to the next generation as elite individuals. In order to show that our approach c an handle multi-objective optimization problems with concave Pareto fr onts, we apply the proposed genetic algorithm to a two-objective funct ion optimization problem with a concave Pareto front. Last, the perfor mance of our multi-objective genetic algorithm is examined by applying it to the flowshop scheduling problem with two objectives: to minimiz e the makespan and to minimize the total tardiness. We also apply our algorithm to the flowshop scheduling problem with three objectives: to minimize the makespan, to minimize the total tardiness, and to minimi ze the total flowtime. Copyright (C) 1996 Elsevier Science Ltd