Multiple attribute decision-making methods for the dynamic operator allocation problem

Taho Yang, Mu Chen Chen, Chih Ching Hung

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)


This study explores two multiple attribute decision-making (MADM) methods to solve a dynamic operator allocation problem. Both methods use an analytic hierarchy process (AHP) to determine attribute weights a priori. The first method uses a technique for order preference by similarity to ideal solution (TOPSIS). The second method incorporates a fuzzy-based logic that uses linguistic variable representation, fuzzy operation, and fuzzy defuzzification. The TOPSIS uses deterministic performance ratings and attribute weights, whilst the fuzzy-based is a linguistic method. An applied case study drawn from existing literature is used to demonstrate and test findings. The proposed methods systematically evaluate alternative scenarios, with the result indicating promise for solving an operator allocation decision problem.

Original languageEnglish
Pages (from-to)285-299
Number of pages15
JournalMathematics and Computers in Simulation
Issue number5
Publication statusPublished - 2007 Jan 10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science
  • Numerical Analysis
  • Modelling and Simulation
  • Applied Mathematics


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