Prudent constraint‐handling technique for multiobjective propeller optimisation

The paper presents an alternative constraint‐handling technique that converts a nonlinear constrained programming problem into an unconstrained multi‐objective optimisation problem. The technique is derived from the behavioural memory constraint‐handling method, which was originally implemented for single‐objective optimisation with genetic algorithms. We compare our presented technique with two other popular constraint‐handling concepts and demonstrate its superiority over them when applied to a propeller optimisation problem. We conclude that the multi‐objective behavioural memory constraint‐handling technique conjugated with the non‐dominated sorting genetic algorithm (NSGA‐II) is a prudent method to apply to problems with an infeasible initial design and where constraints have a natural order of satisfaction, which, if not conformed to, would lead to unrealistic designs that impair the search by GA.