Incorporating preferential weights as a benchmark into a Sequential Reference Point Method

Mariano Jiménez, Amelia Bilbao-Terol and Mar Arenas-Parra

European Journal of Operational Research, 2021, vol. 291, issue 2, 575-585

Abstract: In multi-objective optimization models, it is common that the decision maker expresses the relative importance of objectives through a weighting scheme. However, many solving techniques do not assure that the corresponding solution fits the preferential weights. It could be the case that an objective with a very low weight achieves a good value, whereas another with a high weight yields a very poor achievement. In order to overcome the aforementioned drawback, this paper proposes a new resolution method based on the well-known Reference Point Method. The methodology consists in generating a sequence of Reference Point Method models which share the same reference point fixed at the vector of preferential weights. In the iterative process, the projection direction on the Pareto frontier changes in each iteration according to the deviations between the preferential weights and the current normalised objective values. In this way, a sequence of Pareto-efficient solutions is generated which converges towards a solution that best fits the decision maker's preferential weights. The proposed method is illustrated by means of a numerical example. In order to show its feasibility and usefulness, the methodology is applied to a portfolio selection problem where the corporate sustainability performance of each firm is taken into account.

Keywords: Multi-objective optimisation; Pareto optimality; Preferential weights; Reference point method (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221720300400
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:291:y:2021:i:2:p:575-585

DOI: 10.1016/j.ejor.2020.01.019

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().