Constraint handling in multiobjective genetic algorithms
A. Kurapati, Shapour Azarm, Jin Wu · 8th Symposium on Multidisciplinary Analysis and Optimization · 2000
Four constraint handling improvements to a baseline Multi-Objective Genetic Algorithm (MOGA) are presented in this paper. They are to handle engineering design problems with multiple objectives that are at least partly conflicting, multiple constraints and a mix of continuous and discrete design variables. Two engineering examples, design of a speed reducer and a fleet of ships, are used to demonstrate the suggested approaches. The emphasis in the examples is on the approaches and not on the details per se