Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations

Tim Holzmann and J.C. Smith

European Journal of Operational Research, 2018, vol. 271, issue 2, 436-449

Abstract: In this paper we present the modified augmented weighted Tchebychev norm, which can be used to generate a complete efficient set of solutions to a discrete multi-objective optimization problem. We contribute a generating algorithm that will, without supervision, generate the entire non-dominated set for any number of objectives. To our knowledge, this is the first generating method for general discrete multi-objective problems that uses a variant of the Tchebychev norm. In a computational study, our algorithm’s running times are comparable to previously proposed algorithms.

Keywords: Multiple objective programming; Tchebychev norm; Computational optimization; Generating methods (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:271:y:2018:i:2:p:436-449

DOI: 10.1016/j.ejor.2018.05.036

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