Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making


Lo H., Liaw C., Gul M., Lin K.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.162, 2021 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 162
  • Publication Date: 2021
  • Doi Number: 10.1016/j.cie.2021.107756
  • Journal Name: COMPUTERS & INDUSTRIAL ENGINEERING
  • Journal Indexes: Science Citation Index Expanded, Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: Sustainable, Supplier selection, Transportation planning, Supply chain network, MCDM, Manufacturing, DATA ENVELOPMENT ANALYSIS, PERFORMANCE EVALUATION, FUZZY APPROACH, MCDM MODEL, SELECTION, ENTERPRISES, MANAGEMENT, INNOVATION, FRAMEWORK

Abstract

Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max-min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.