GESAS II: A Better Relationship between Efficiency and Efficacy While Experimenting with Simulation Models

Abstract

A general methodology that solves the decision-making problem associated with simulation models is needed to find a very good compromise solution between efficacy and efficiency. Several methodologies in the literature try to solve the problem, but every one of them includes hypotheses that usually hamper efficacy by improving efficiency. GESAS, first, and GESAS II, now, try to use the constantly improving power of computers to examine as many alternatives as possible, with the aim of exhaustive evaluation of alternatives for medium-size problems. The objective is to develop a efficient rejection algorithm by reducing the necessary number of repetitions to analyze the subpar alternatives. Several methodologies are tested against the common example of inventory control, which includes in this case three input variables (that account for 2646 different alternatives) and two competing criteria.

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References

[1] Otamendi, J. 1999. GESAS methodology: A methodology for the generation, evaluation and selection of alternatives via simulation . SIMULATION 73 (2): 91-99 .

[2] Zeleny, M. 1982. Multiple criteria decision making. New York: McGraw-Hill .

[3] Barba-Romero, S., and J. C. Pomerol. 1997. Decisiones Multicriterio: Fundamentos TeÛricos y UtilizaciÛn Pr·ctica. Alcal· de Henares: Universidad de Alcal·.

[4] Taha, H. 1988. Simulation modelling and SIMNET. Englewood Cliffs, NJ: Prentice Hall .

[5] Law, A., and W. D. Kelton. 1991. Simulation model and analysis. NewYork: McGraw-Hill .

[6] Badri, M. A. 1999. A simulation model for multi-product inventory control management . SIMULATION 72 (1): 20-32 .

[7] Otamendi, J. 2001. TÈcnicas de SimulaciÛn Avanzada para el Tratamiento de Situaciones de Riesgo. Cartagena: Universidad PolitÈcnica de Cartagena.

[8] Rees, L. P., E. R. Clayton, and B. W. Taylor III. 1985. Solving multiple response simulation models using a modified response surface methodology within a lexicographic goal programming framework . IIE Transactions 17: 47-57 .

[9] Fern·ndez de la Puebla, J. 1996. Analysis of multiresponse simulation models based on the variability of the results. In Proceedings of the 1996 Simulation Multiconference, April 8-11, New Orleans, LA.