The multi-objective label correcting algorithm for supply chain modeling

Wen-Yau Liang, Chun Che Huang, Yin Chen Lin, Tsun Hsien Chang, Meng Hao Shih

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Purpose - The purpose of this paper is to provide a multi-objective label correcting algorithm (MLC) to solve supply chain modeling problems. Design/methodology/approach - In the study, the proposed approach extends label correcting algorithm to apply to multi-objective problems where various conflicting objectives have to be considered simultaneously so as to make a trade-off between different criteria at the same time. The algorithm performs a forward search from a selected output point to all accessible points. It processes the stack of nodes based on the last-in-first-out (LIFO) rule. For the serial way, a node in the stack is pulled out for exploration and its subsequent node(s) is (are) pushed into the stack in each iteration. Then the MLC determines and updates the paths. The algorithm terminates when all nodes in the stack are pulled. Findings - The paper demonstrates that the MLC methodology can successfully resolve the supplier selection problem by taking into account the preference of the decision makers. Originality/value - many researches had proposed that many areas of the industry as, for example, telecommunications, transportation, aeronautics, chemistry, mechanical, and environment, deal with multi-objective, where various conflicting objectives have to be considered simultaneously. The method presented in the paper will help future studies in modeling of supply chain.

Original languageEnglish
Pages (from-to)172-178
Number of pages7
JournalInternational Journal of Production Economics
Volume142
Issue number1
DOIs
Publication statusPublished - 2013 Mar 1

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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