The Design of Open Engineering Systems Lab

University at Buffalo - The State University of New York

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Effective Generation of Pareto Sets Using Genetic Programming

Research Area: Research Publication Year: 2001
Type of Publication: Technical Report Keywords: Genetic Algorithms, Heuristic Optimization Multi Objective Optimization MOGA Pareto Frontiers
Authors: Eddy, John; Lewis, Kemper
Abstract:
Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances of the individual subsystems. It then becomes necessary to consider the tradeoffs that occur in a multi-objective design problem. The complete solution to a multi-objective optimization problem is the entire set of non-dominated configurations commonly referred to as the Pareto set. Common methods of generating points along a Pareto frontier involve repeated conversion of multi-objective problems into single objective problems using weights. These methods have been shown to perform poorly when attempting to populate a Pareto frontier. This work presents an efficient means of generating a thorough spread of points along a Pareto frontier using genetic programming
Comments:
Design Automation Conference

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