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Cross entropy for multiobjective combinatorial optimization problems with linear relaxations

Rafael Caballero, Alfredo Hernandez-Diaz (), Manuel Laguna and Julián Molina

European Journal of Operational Research, 2015, vol. 243, issue 2, 362-368

Abstract: While the cross entropy methodology has been applied to a fair number of combinatorial optimization problems with a single objective, its adaptation to multiobjective optimization has been sporadic. We develop a multiobjective optimization cross entropy (MOCE) procedure for combinatorial optimization problems for which there is a linear relaxation (obtained by ignoring the integrality restrictions) that can be solved in polynomial time. The presence of a relaxation that can be solved with modest computational time is an important characteristic of the problems under consideration because our procedure is designed to exploit relaxed solutions. This is done with a strategy that divides the objective function space into areas and a mechanism that seeds these areas with relaxed solutions. Our main interest is to tackle problems whose solutions are represented by binary variables and whose relaxation is a linear program. Our tests with multiobjective knapsack problems and multiobjective assignment problems show the merit of the proposed procedure.

Keywords: Multiobjective combinatorial optimization; Cross entropy; EMO; Linear relaxation (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:243:y:2015:i:2:p:362-368

DOI: 10.1016/j.ejor.2014.07.046

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

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