Data envelopment analysis and Pareto genetic algorithm applied to robust design in multiresponse systems.

Canessa-Terrazas, Enrique Carlos; de Mateo-Gómez, Filadelfo; Yushimito-Del Valle, Wilfredo Fernando

This paper shows the use of Data Envelopment Analysis (DEA) to rank and select the solutions found by a Pareto Genetic Algorithm (PGA) to problems of robust design in multiresponse systems with many control and noise factors. The efficiency analysis of the solutions using DEA shows that the PGA finds a good approximation to the efficient frontier. Additionally, DEA is used to determine the combination of a given level of mean adjustment and variance in the responses of a system, so as to minimize the economic cost of achieving those two objectives. By linking that cost with other technical and/or economic considerations, the solution that best matches a predefined level of quality can be more sensibly selected.

DATA envelopment analysis; GENETIC algorithms; TAGUCHI methods; ROBUST control; MATHEMATICAL optimization

Revista Facultad de Ingeniería Universidad de Antioquia, 2016, Issue 79, p119

0120-6230

Academic Journal

10.17533/udea.redin.n79a11