Multi-objective supplier selection process: a simulation-optimization framework integrated with MCDM


Kabadayi N., Dehghanimohammadabadi M.

ANNALS OF OPERATIONS RESEARCH, vol.319, no.2, pp.1607-1629, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 319 Issue: 2
  • Publication Date: 2022
  • Doi Number: 10.1007/s10479-021-04424-2
  • Journal Name: ANNALS OF OPERATIONS RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Computer & Applied Sciences, INSPEC, Public Affairs Index, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.1607-1629
  • Keywords: Supplier selection, Simheuristics, Simio-MATLAB integration, TOPSIS, NSGA-II, GENETIC ALGORITHM, DECISION-MAKING, CHAIN CONFIGURATION, FUZZY TOPSIS, METHODOLOGY, SYSTEM, MODEL, AHP
  • Istanbul University Affiliated: Yes

Abstract

As a multi-criteria decision-making (MCDM) problem, supplier selection plays a key role in achieving the objectives of a supply chain system. Multiple strategic, operational, quantitative, and qualitative criteria influence the supplier selection process. A wide spectrum of criteria have been introduced, classified, and used by researchers and practitioners to evaluate the suppliers' performance; however, measuring and employing all of these criteria is impractical in real-world scenarios due to the budget, time, and information limitations. In this study, a decision support system (DSS) is developed, which helps managers to select a set of most effective criteria for the supplier selection process. This DSS is a threefold integration of MCDM and simulation and optimization. In this framework, the MCDM module incorporates a combination of criteria to select the suppliers. Then, a simulation model is used to evaluate the performance of the supply chain system considering the selected suppliers. Based on the simulation results, a multi-objective metaheuristic algorithm is utilized to find the ideal combinations of the criteria to maximize the supply chain system performance.