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Acta Mathematica Vietnamica

, Volume 42, Issue 1, pp 1–25 | Cite as

A New Method for Determining all Maximal Efficient Faces in Multiple Objective Linear Programming

  • Ta Van TuEmail author
Article
  • 115 Downloads

Abstract

Most of the known methods for finding the efficient set of a multiple objective linear programming (MOLP) problem are bottom-up search methods. Main difficulties of the known bottom-up search methods are to find all efficient extreme points adjacent to and to enumerate all efficient faces incident to an efficient degenerate extreme point. Main drawbacks of these methods are that the computational cost is still large and an implementation of them is still difficult. In this paper we propose a new local bottom-up search method for finding all maximal efficient faces for an MOLP problem. Our method is based on the maximal descriptor index sets for efficient edges and extreme rays for the MOLP problem in which the maximal descriptor index sets for edges and extreme rays incident to an efficient degenerate extreme point are easily found on the basis of solving some special linear programming problems. In addition, all efficient extreme points adjacent to and all efficient faces incident to an efficient extreme point can be easily found without using the simplex tables corresponding to bases of this point. Our method can overcome difficulties caused by the degeneracy of faces and is easy to implement. Some comparisons of our method with the known bottom-up search methods are presented. A numerical example is given to illustrate the method.

Keywords

Multiple objective programming Maximal efficient face Maximal descriptor index set for a face 

Mathematics Subject Classification (2010)

90C29 90C90 

Notes

Acknowledgments

I would like to thank a referee for his helpful and valuable comments which greatly improved the presentation of the paper.

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Copyright information

© Institute of Mathematics, Vietnam Academy of Science and Technology (VAST) and Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.Department of Operations ResearchCorvinus University of BudapestBudapestHungary

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