Extension of the Directed Search Domain algorithm for multi-objective optimization to higher dimensions-Reference-Cited by-同舟云学术

Extension of the Directed Search Domain algorithm for multi-objective optimization to higher dimensions

Published:2024-06-27 Issue:2-3 Volume:340 Page:1125-1160
ISSN:0254-5330
Container-title:Annals of Operations Research
language:en
Short-container-title:Ann Oper Res

Author:

Yu Boxi^ORCID,Utyuzhnikov Sergey^ORCID

Abstract

AbstractThis paper addresses the problem of generating an evenly distributed set of Pareto solutions. It appears in real-life applications related to multi-objective optimization when it is important to represent the entire Pareto front with a minimal cost. There exist only a few algorithms which are able to tackle this problem in a general formulation. The Directed Search Domain (DSD) algorithm has proved to be efficient and quite universal. It has successfully been applied to different challengeable test cases. In this paper for the first time the DSD approach is systematically extended and applied to problems with higher dimensions. The modified algorithm does not have any formal limitation on the number of objective functions that is important for practical applications. The efficacy of the algorithm is demonstrated on a number of test cases.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10479-024-06117-y.pdf

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