International Journal of Computational Intelligence Systems

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Volume 11, Issue 1, 2018, Pages 1123 - 1141

A case retrieval method combined with similarity measurement and DEA model for alternative generation

Authors
Jing ZHENG1, 2, *, zhengjing80@fjjxu.edu.cn, Ying-Ming WANG2, msymwang@hotmail.com, Kai ZHANG3, k7920@qq.com
1College of Electronics and Information Science, Fujian Jiangxia University, Fujian 350108, P. R. China;
2Decision Sciences Institute, Fuzhou University, Fujian 350116, P. R. China;
3Department of Information Engineering, Fujian Chuanzheng Communications College, Fuzhou 350007, PR China.
*Corresponding author.
Corresponding Author
Received 10 December 2017, Accepted 5 May 2018, Available Online 21 May 2018.
DOI
10.2991/ijcis.11.1.85How to use a DOI?
Keywords
Case-based reasoning; DEA model; multiple criteria decision analysis; prospect theory; similarity measurement
Abstract

In alternative generation, reusing past experience is a potential methodology and case retrieval is a primary step. In order to improve the performance of case retrieval process, many applications have used different similarity measurements and the selection method for the most suitable historical case to solve problems. Many investigations have shown that human beings are usually bounded rational and their psychological behavior has certain influence on decision making. However, such behavior is neglected in similarity measurements and the selection method can only deal with the evaluation given by one decision maker (DM). This paper proposes a new case retrieval method that combines similarity measurement and data envelopment analysis (DEA) model. A similarity measurement based on cumulative prospect theory is proposed to consider the DM’s psychological behavior. A hybridization of four similarity measurements is used to generate a set of similar historical cases. The DM evaluates the similar historical case set by a pairwise comparison matrix. A DEA model is constructed to get the priority vector. The most suitable historical case can then be picked out through the case similarity and the case priority. A case study is finally introduced to illustrate the use of the proposed method.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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<Previous Article In Issue
Next Article In Issue>
Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
1123 - 1141
Publication Date
2018/05/21
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.11.1.85How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Jing ZHENG
AU  - Ying-Ming WANG
AU  - Kai ZHANG
PY  - 2018
DA  - 2018/05/21
TI  - A case retrieval method combined with similarity measurement and DEA model for alternative generation
JO  - International Journal of Computational Intelligence Systems
SP  - 1123
EP  - 1141
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.85
DO  - 10.2991/ijcis.11.1.85
ID  - ZHENG2018
ER  -