Discrete representation of non-dominated sets in multi-objective linear programming
Lizhen Shao and
Matthias Ehrgott
European Journal of Operational Research, 2016, vol. 255, issue 3, 687-698
Abstract:
In this paper we address the problem of representing the continuous but non-convex set of non-dominated points of a multi-objective linear programme by a finite subset of such points. We prove that a related decision problem is NP-complete. Moreover, we illustrate the drawbacks of the known global shooting, normal boundary intersection and normal constraint methods concerning the coverage error and uniformity level of the representation by examples. We propose a method which combines the global shooting and normal boundary intersection methods. By doing so, we overcome their limitations, but preserve their advantages. We prove that our method computes a set of evenly distributed non-dominated points for which the coverage error and the uniformity level can be guaranteed. We apply this method to an optimisation problem in radiation therapy and present illustrative results for some clinical cases. Finally, we present numerical results on randomly generated examples.
Keywords: Multi-objective optimisation; Linear programming; Non-dominated set; Discrete representation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (12)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:255:y:2016:i:3:p:687-698
DOI: 10.1016/j.ejor.2016.05.001
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