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A new bottom-up search method for determining all maximal efficient faces in multiple objective linear programming

Ta Van Tu (t_vantu***at***yahoo.com)

Abstract: Bottom-up search methods for determining the efficient set of a multiple objective linear programming (MOLP) problem have a valuable advantage that they can quickly give efficient subsets of the MOLP problem to the decision makers. Main difficulties of the previously appeared bottom-up search methods are finding all efficient extreme points adjacent to and enumerating 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 of an MOLP problem. Our method is based on the maximal descriptor index sets for efficient edges and extreme rays of 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; 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 easily overcome difficulties caused by the degeneracy of faces and is easy to implement. Some comparisons of our method with the previously appeared bottom-up search methods are presented. A numerical example is given to illustrate the method.

Keywords: multiple objective programming; maximal efficient faces; maximal descriptor index set for a face AMS Subject Classifications: 90C29; 90C50; 90C90

Category 1: Other Topics (Multi-Criteria Optimization )

Citation:

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Entry Submitted: 11/04/2014
Entry Accepted: 11/04/2014
Entry Last Modified: 11/06/2014

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