New constraint-handling method for multi-objective and multi-constraint evolutionary optimization

Abstract

A new constraint-handling method based on Pareto-optimality and niching concepts for multi-objective multiconstraint evolutionary optimization is proposed. The proposed method does not require any constants to be tuned for constraint-handling. In addition, the present method does not use the weighted-sum of constraints and thus does not require tuning of weight coefficients and is efficient even when all individuals in the initial population are infeasible or the amount of violation of each constraint is significantly different. The proposed approach is demonstrated to be remarkably more robust than the dynamic penalty approach and other dominance-based approaches through the optimal design of a welded beam and conceptual design optimization of a two-stage-to-orbit spaceplane. © 2007 The Japan Society for Aeronautical and Space Sciences.