Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective optimization, UPS-EMOA

Authors:
T. Aittokoski;K. Miettinen
Affiliations:
Department of Mathematical Information Technology, FI-40014 University of Jyvaskyla, Finland;Department of Mathematical Information Technology, FI-40014 University of Jyvaskyla, Finland
Venue:
Optimization Methods & Software - The International Conference on Engineering Optimization (EngOpt 2008)
Year:
2010

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Abstract

Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.