Multiobjective optimization using adaptive range genetic algorithms with data envelopment analysis

The present paper describe an implementation of the adaptive range genetic algorithms (ARange GAs) in multi-objective optimization by using the data envelopment analysis (DEA). ARange GAs is a new genetic search algorithms which adapt the searching range according to the optimization situation and make it possible to obtain highly accurate results effectively. DEA is to measure the efficiency of decision making units, and it is used mainly in the field of economy. When we combine both methods, we can obtain a great number of Pareto solutions, that might give an important aspect of the design, within a single GAs process effectively. The purpose of this study is to verify the characteristics and effectiveness of the proposed method through demonstrative examples.