Abstract
We present a new method for generating a concise and representative approximation of the (weakly) efficient set of a nonlinear multi-objective optimization problem. For the parameter dependent ε-constraint scalarization an algorithm is given which allows an adaptive controlling of the parameters—the upper bounds—based on sensitivity results such that equidistant approximation points are generated. The proposed method is applied to a variety of test-problems.
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Eichfelder, G. (2009). A Constraint Method in Nonlinear Multi-Objective Optimization. In: Barichard, V., Ehrgott, M., Gandibleux, X., T'Kindt, V. (eds) Multiobjective Programming and Goal Programming. Lecture Notes in Economics and Mathematical Systems, vol 618. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85646-7_1
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DOI: https://doi.org/10.1007/978-3-540-85646-7_1
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