Efficient computation of the search region in multi-objective optimization

Kerstin Dächert, Kathrin Klamroth, Renaud Lacour and Daniel Vanderpooten

European Journal of Operational Research, 2017, vol. 260, issue 3, 841-855

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.

Keywords: Multi-objective optimization; Nondominated set; Search region; Local upper bounds; Scalarization (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:260:y:2017:i:3:p:841-855

DOI: 10.1016/j.ejor.2016.05.029

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