Mathematical Methods of Operations Research

, Volume 87, Issue 2, pp 251–283 | Cite as

Variants of the \( \varepsilon \)-constraint method for biobjective integer programming problems: application to p-median-cover problems

Original Article
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Abstract

We conduct an in-depth analysis of the \(\varepsilon \)-constraint method (ECM) for finding the exact Pareto front for biobjective integer programming problems. We have found up to six possible different variants of the ECM. We first discuss the complexity of each of these variants and their relationship with other exact methods for solving biobjective integer programming problems. By extending some results of Neumayer and Schweigert (OR Spektrum 16:267–276, 1994), we develop two variants of the ECM, both including an augmentation term and requiring \(N+1\) integer programs to be solved, where N is the number of nondominated points. In addition, we present another variant of the ECM, based on the use of elastic constraints and also including an augmentation term. This variant has the same complexity, namely \(N+1\), which is the minimum reached for any exact method. A comparison of the different variants is carried out on a set of biobjective location problems which we call p-median-cover problems; these include the objectives of the p-median and the maximal covering problems. As computational results show, for this class of problems, the augmented ECM with elastic constraint is the most effective variant for finding the Pareto front in an exact manner.

Keywords

Biobjective integer programming Epsilon-constraint method p-Median-cover problem 

Notes

Acknowledgements

The authors wish to thank the anonymous referees for their useful suggestions and comments that improved the paper, and to FICO for providing the Xpress Optimizer application, which has been used to obtain the computational results.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Statistics and Operational ResearchUniversity of ValladolidValladolidSpain
  2. 2.Department of Statistics and Operational ResearchPublic University of NavarreTudelaSpain

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