Multiobjective optimization: Quasi-even generation of pareto frontier and its local approximation

Sergei V. Utyuzhnikov

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)


In multidisciplinary optimization the designer needs to fi d a solution to an optimization problem that includes a number of usually contradicting criteria. Such a problem is mathematically related to the fiel of nonlinear vector optimization with constraints. It is well-known that the solution to this problem is far from unique and given by a Pareto surface. In the real-life design the decision-maker is able to analyze only several Pareto optimal (trade-off) solutions. Therefore, a well-distributed representation of the entire Pareto frontier is especially important. At present, there are only a few methods that are capable of even generating a Pareto frontier in a general formulation. In the present work they are compared to each other, with the main focus being on a general strategy combining the advantages of the known algorithms. The approach is based on shrinking a search domain to generate a Pareto optimal solution in a selected area on the Pareto frontier. The search domain can be easily conducted in the general multidimensional formulation. The efficien y of the method is demonstrated on different test cases. For the problem in question, it is also important to carry out a local analysis. This provides an opportunity for a sensitivity analysis and local optimization. In general, the local approximation of a Pareto frontier is able to complement a quasi-even generated Pareto set.

Original languageEnglish
Title of host publicationHandbook of Optimization Theory
Subtitle of host publicationDecision Analysis and Application
PublisherNova Science Publishers, Inc.
Number of pages25
ISBN (Print)9781608765003
Publication statusPublished - Jan 2011
Externally publishedYes


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