A fuzzy matching model with Hurwicz criteria for one-shot multi-attribute exchanges in E-brokerage

Abstract

The trade determination problem is an important decision problem for multi-attribute exchanges in E-brokerages. As of now, some studies have focused on this issue. However, theories and guidelines for the trade determination problem under fuzzy environments are still sparse. In this paper, taking into account the fuzzy information involved in one-shot multi-attribute exchanges, a new fuzzy matching model is proposed for the trade determination problem. In the model, we present a novel calculation method of the matching degree based on the improved fuzzy information axiom as a baseline study. Also, the credibility measure and Hurwicz criterion are introduced to convert the model into a crisp one. Since the crisp model is a 0-1 integer programming problem, the commonly used branch and bound algorithm and related optimization techniques become applicable. Finally, an example is employed to illustrate the application and sensitivity analysis of the proposed model.

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