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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4095 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4095 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4095 archive 351 disk0/00/00/45/46 2016-01-15 02:06:12 2021-08-27 17:15:19 2016-01-15 02:06:12 monograph show 2 Sun M. Stam A. 1602 Steuer R.E. Solving Multiple Objective Programming Problems Using Feed-Forward Artificial Neural Networks: The Interactive FFANN Procedure pub iis_cmp iis_inn iis_met prog_mda 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 1983). From the computational results, the Interactive FFANN Procedure produces good results and is robust with regard to the neural network architecture. 1995-05 published WP-95-046 WP-95-046 10 1588 public working_paper IIASA, Laxenburg, Austria 32 FALSE info:eu-repo/semantics/book