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

Boxi Yu () and Sergey Utyuzhnikov ()
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Boxi Yu: University of Manchester
Sergey Utyuzhnikov: University of Manchester

Annals of Operations Research, 2024, vol. 340, issue 2, No 15, 1125-1160

Abstract: Abstract This 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.

Keywords: Multi-objective optimization; Directed Search Domain; Pareto set; Evenly distributed set; Many-objective optimization problem (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-024-06117-y

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