A Multi-Objective Optimization Method Combining Generalized Data Envelopment Analysis and Genetic Algorithms
Yeboon Yun, Hirotaka Nakayama, Tetsuzo Tanino, Masao ARAKAWA · Transactions of the Institute of Systems Control and Information Engineers · 2000
In this paper, a method using generalized data envelopment analysis and genetic algorithms is proposed for finding efficient frontiers in multi-objective optimization problems. The proposed method can yield desirable efficient frontiers even in nonconvex cases. It will be proved that the proposed method overcomes shortcomings of existing methods through several numerical examples.