Solving Multiple Objective Programming Problems Using Feed-Forward Artificial Neural Networks: The Interactive FFANN Procedure

Minghe Sun, Antonie Stam and Ralph E. Steuer
Additional contact information
Minghe Sun: Division of Management and Marketing, College of Business, University of Texas at San Antonio, San Antonio, Texas 78249
Antonie Stam: International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria and Department of Management, Terry College of Business, University of Georgia, Athens, Georgia 30602
Ralph E. Steuer: Faculty of Management Science, Brooks Hall, University of Georgia, Athens, Georgia 30602

Management Science, 1996, vol. 42, issue 6, 835-849

Abstract: In this paper, we propose a new interactive procedure for solving multiple objective programming problems. Based upon feed-forward artificial neural networks (FFANNs), the method is called the Interactive FFANN Procedure. In the procedure, the decision maker articulates preference information over representative samples from the nondominated set either by assigning preference "values" to the sample solutions or by making pairwise comparisons in a fashion similar to that in the Analytic Hierarchy Process. With this information, a FFANN is trained to represent the decision maker's preference structure. Then, using the FFANN, an optimization problem is solved to search for improved solutions. An example is given to illustrate the Interactive FFANN Procedure. Also, the procedure is compared computationally with the Tchebycheff Method (Steuer and Choo [Steuer, R. E., E.-U. Choo. 1983. An interactive weighted Tchebycheff procedure for multiple objective programming. Math. Programming 26(1) 326--344.]). The computational results indicate that the Interactive FFANN Procedure produces good solutions and is robust with regard to the neural network architecture.

Keywords: multiple objective programming; feed-forward artificial neural networks; multiple criteria decision making; analytic hierarchy process; interactive procedures (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.42.6.835 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:42:y:1996:i:6:p:835-849

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().