Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4959668 | European Journal of Operational Research | 2017 | 35 Pages |
Abstract
Multi-objective optimization procedures usually proceed by iteratively producing new solutions. For this purpose, a key issue is to determine and efficiently update the search region, which corresponds to the part of the objective space where new nondominated points could lie. In this paper we elaborate a specific neighborhood structure among local upper bounds. Thanks to this structure, the update of the search region with respect to a new point can be performed more efficiently compared to existing approaches. Moreover, the neighborhood structure provides new insight into the search region and the location of nondominated points.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Kerstin Dächert, Kathrin Klamroth, Renaud Lacour, Daniel Vanderpooten,