MOSES: A MULTIOBJECTIVE OPTIMIZATION TOOL FOR ENGINEERING DESIGN

Abstract

This paper introduces a multiobjective optimization tool called MOSES (Multiobjective Optimization of Systems in the Engineering Sciences). This tool is a convenient testbed for analyzing the performance of new and existing multicriteria optimization techniques, and it is an effective engineering design tool. Two new multiobjective optimization techniques based on the genetic algorithm (GA) are introduced, and two engineering design problems are solved using them. These methods are based in the concept of min-max optimum, and can produce the Pareto set and the best trade-off among the objectives. The results produced by these approaches are compared to those produced with other mathematical programming techniques and GA-based approaches, showing the new techniques' capability to generate better trade-offs than the approaches previously reported in the literature.

Keywords:

• Multiobjective optimization
• genetic algorithms
• min-max optimization
• multicriteria optimization
• artificial intelligence

Additional information

Notes on contributors

CARLOS A. COELLO COELLO

Corresponding author.