A Generation Method of Case Study Data for DEA

Abstract

This paper addresses a generation method on case data for DEA(Data Envelopment Analysis) study using “agents”. Books include some useful business scenario cases and data for a learner to try analysis based on his/her knowledge, however, they are in a sense limited examples to understand deeply the way of DEA. Since generation of various and appropriate cases takes much time and cost, there exists strong need to generate such cases automatically. We propose agent-based software framework to provide various example cases of business scenario and data, which includes self-validated functionalities. Decision tree analysis and evolutionary computational methods are used to construct our software framework, and experimental results show its effectiveness.