A Comprehensive Evaluation Method for Cross-Organizational Service Selection

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-11 DOI:10.1109/CSE.2010.54

Rutao Yang, Lianyong Qi, Wenmin Lin, Wanchun Dou, Jinjun Chen

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引用次数: 1

Abstract

Service selection has become a key step for cross-organizational collaboration in service-oriented practices and gained ever-increasing attention in both academic and industrial domains. However, the organizations involved may hold different types of evaluation scores, e.g., crisp number, value range and fuzzy linguistic terms. Besides, for the scores of fuzzy linguistic terms, different organizations may hold various evaluation granularities to meet their personalized preferences, which further increase the difficulties for unified service evaluation. So it is a great challenge to take these aspects into consideration for cross-organizational service selection. In view of this challenge, a comprehensive evaluation method named CRML (Crisp number-value Range-Multiple granularities Linguistic terms, CRML) is put forward in this paper. First, the scores of various evaluation types are unified into a form of trapezoidal fuzzy numbers. Second, a classic TOPSIS method is employed to rank all the candidate services for cross-organizational service selection. Finally, a case study is brought forth to validate the feasibility of our proposal.

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跨组织服务选择的综合评价方法

服务选择已经成为面向服务实践中跨组织协作的关键步骤，在学术界和工业界都受到越来越多的关注。然而，所涉及的组织可能持有不同类型的评价分数，例如，明确的数字，价值范围和模糊的语言术语。此外，对于模糊语言术语的评分，不同组织可能会根据其个性化偏好持有不同的评价粒度，这进一步增加了统一服务评价的难度。因此，在跨组织的服务选择中考虑这些方面是一个很大的挑战。针对这一挑战，本文提出了一种名为CRML (Crisp number-value Range-Multiple gran粒度Linguistic terms，简称CRML)的综合评价方法。首先，将各种评价类型的得分统一为梯形模糊数的形式。其次，采用经典的TOPSIS方法对所有候选服务进行排序，以进行跨组织服务选择。最后，通过案例分析验证了该方案的可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2010 13th IEEE International Conference on Computational Science and Engineering

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