Pareto layer: Its formulation and search by way of evolutionary multi-objective optimization

Gideon Avigad*, Erella Eisenstadt, Alexander Goldvard

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This article examines multi-objective problems where a solution (product) is related to a cluster of performance vectors within a multi-objective space. Here the origin of such a cluster is not uncertainty, as is typical, but rather the range of performances attainable by the product. It is shown that, in such cases, comparison of a solution to other solutions should be based on its best performance vectors, which are extracted from the cluster. The result of solving the introduced problem is a set of Pareto optimal solutions and their representation in the objective space, which is referred to here as the Pareto layer. The authors claim that the introduced Pareto layer is a previously unattended novel representation. In order to search for these optimal solutions, an evolutionary multi-objective algorithm is suggested. The article also treats the selection of a solution from the obtained optimal set.

Original languageEnglish
Pages (from-to)453-470
Number of pages18
JournalEngineering Optimization
Issue number5
StatePublished - May 2010
Externally publishedYes


  • Multi-objective
  • Pareto
  • Robotics


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