A comparator-based constraint handling technique for evolutionary algorithms

Abstract

Constraint handling is a key task for the successful optimization of design parameters in industrial design problems. This paper proposes a comparator-based constraint handling technique, called the More Less-Violations Method (MLVM), for solving real constrained optimization problems using evolutionary algorithms. The structure of the MLVM is simple and it can easily be integrated into conventional evolutionary algorithms. In the proposed method, constraint weights represent the level of importance of each constraint, enabling evolutionary compliance prioritization. Moreover, an acceptable region formed by the constraint tolerances allows trade-offs between objectives and constraints while preserving diverse solutions and improving optimization performance. These elements enable the appropriate design of industrial optimization problems. An application of this method to problems without constraint tolerances is also proposed. The JAXA/Mazda benchmark problem, developed on a real-world constrained design optimization dataset, is used to assess the performance of the MLVM. The results indicate that the MLVM realizes encouraging optimization performance.

A formulation of industrial conceptual design optimization problem for commercial transport airplanes with turboelectric propulsion

“…Its strong search bias toward the acceptable region provides a robustness as well as an efficiency in solving design optimization problems with numerous constraints, such as airplane conceptual design optimization problems. The MLVM module, written in Fortran, is available online at Takami (2022).…”

A Formulation of the Industrial Conceptual Design Optimization Problem for Commercial Transport Airplanes

“…Efficiency in addition to robustness is required to search for and find the desired feasible solutions within a limited product-development timeframe. In the CMOGA, the more less-violations method (MLVM) [39] is used as the CHT. The MLVM is an efficient and robust CHT developed by the authors for EAs.…”