Constraint handling improvements for multiobjective genetic algorithms

Authors:
A. Kurpati;S. Azarm;J. Wu
Affiliations:
Department of Mechanical Engineering, University of Maryland, College Park, MD 20742---3035, USA e-mail: azarm@eng.umd.edu, US;Department of Mechanical Engineering, University of Maryland, College Park, MD 20742---3035, USA e-mail: azarm@eng.umd.edu, US;Department of Mechanical Engineering, University of Maryland, College Park, MD 20742---3035, USA e-mail: azarm@eng.umd.edu, US
Venue:
Structural and Multidisciplinary Optimization
Year:
2002

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Abstract

Four constraint handling improvements for Multi-Objective Genetic Algorithms (MOGA) are proposed. These improvements are made in the fitness assignment stage of a MOGA and are all based upon a "Constraint-First-Objective-Next" model. Two multi-objective design optimization examples, i.e. a speed reducer design and the design of a fleet of ships, are used to demonstrate the improvements. For both examples, it is shown that the proposed constraint handling techniques significantly improve the performance of a baseline MOGA.