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Journal of Intelligent Manufacturing

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20-04-2014

The rough set based approach to generic routing problems: case of reverse logistics supplier selection

Authors: Chun-Che Huang, Wen-Yau Liang, Tzu-Liang Tseng, Ping-Houa Chen

Published in: Journal of Intelligent Manufacturing | Issue 4/2016

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Abstract

In recent years, Reverse Logistics (RL) has been touted as one of the strategies of improving organization performance and generating a competitive advantage. In RL, the generic routing problem has become a focus since it provides a great flexibility in modeling, e.g., selection of suppliers by using a node as a supplier candidate in a network. To date, complicated networks make decision makers hard to search a desired routine. In addition, the traditional network defines and resolves such a problem only at one soot. The solution cannot be acquired from multiple perspectives like minimal cost, minimal delivery time, maximal reliability, and optimal “3Rs”—reduce, reuse, and recycle. In this study, rough set theory is applied to reduce complexity of the RL data sets and induct decision rules. Through incorporating the decision rules, the generic label correcting algorithm is used to solve generic routing problems by integrating various operators and comparators in the GLC algorithm. Consequently, the desired RL suppliers are selected.

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Title: The rough set based approach to generic routing problems: case of reverse logistics supplier selection
Authors: Chun-Che Huang
Wen-Yau Liang
Tzu-Liang Tseng
Ping-Houa Chen
Publication date: 20-04-2014
Publisher: Springer US
Published in: Journal of Intelligent Manufacturing / Issue 4/2016
Print ISSN: 0956-5515
Electronic ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-014-0913-8

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