Practical common weights goal programming approach for technology selection

Abstract

A practical common weight goal programming methodology with an improved discriminating power for technology selection is introduced. The proposed goal programming methodology enables the evaluation of the relative eciency of decisionmaking units (DMUs) with respect to multiple outputs and a single exact input with common weights. Its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed goal programming framework with that obtained by the DEA classic model (CCR model) and Minimax method (Karsak and Ahiska (2005)).