Special Issue "Fuzzy Decision-Making Methods for Sustainable Developments of Industrial Engineering"

Special Issue Editors

Prof. Dr. Huchang Liao
Sichuan University, Sichuan, China
E-Mail: liaohuchang@163.com

Dr. Xingli Wu
Sichuan University, Sichuan, China
E-Mail: wuxingliwxl@163.com

Prof. Dr. Abbas Mardani
University of South Florida, Tampa, FL, USA
E-Mail: mabbas3@live.utm.my

Prof. Dr. Dalia Å treimikienÄ—
Vilnius University, Vilnius, Lithuania
E-Mail: dalia.streimikiene@knf.vu.lt

Prof. Dr. Enrique Herrera-Viedma
University of Granada, Granada, Spain
E-Mail: viedma@decsai.ugr.es

Special Issue Information

Decision analysis has been proved to be an excellent operational research direction. After nearly 60 years of development, many multiple criteria decision-making methods that can flexibly handle multi-dimensional and discrete decision-making problems with quantitative or qualitative information have been proposed, including the traditional ones: AHP, ANP, TOPSIS, VIKOR, COPRAS, UTA, MULTIMOORA, MACBETH, DEMATEL, PROMETHEE, ELECTRE, ORESTE, and the recently developed ones: BWM, GLDS, DNMA, SWARA, WASPAS, ARAS. These methods have different emphases and are suitable for solving problems with different conditions and requirements. Especially, these decision-making methods have been generalized to fuzzy contexts and many applications have been achieved in different areas.

Under the background of information, integration, and intelligence, the object of industrial engineering extends from a traditional manufacturing system to a generalized production system including development, design, supply, and sales service. In addition to focusing only on quality and cost, design, production cycle, market response, resource consumption, and environment should also be considered to achieve sustainable development of the entire system. However, integrating multi-dimensional issues into decision making is not easy because it requires policy coherence and linkages between sectors and actors. The challenges include how to develop consistent and easy-to-understand indicators to support decision making, establish monitoring and evaluation processes, track progress towards achieving the sustainable development goals, and strengthen the infrastructure for data collection, analysis, and effective use in decision making. Therefore, powerful operational research tools are needed to solve these decision problems in industrial engineering for decision-makers from a multi-dimensional perspective.

This special issue aims to encourage researchers and practitioners to address challenges associated with fuzzy decision-making methodologies in industrial engineering. We are looking for papers with a focus on fuzzy decision-making methods for solving certain issues in the sustainable developments of industrial engineering with full consideration of the characteristics of these problems so as to meet the requirements of contemporary society. In particular, new interdisciplinary approaches of decision making in industrial engineering, or strong conceptual foundation in newly evolving topics are especially welcome.

Potential topics include but are not limited to the fuzzy decision-making methods in:

  • Facility location and scale decision;
  • Inventory control and supply chain management operations;
  • Business process and performance management;
  • Risk assessment and decision of new product development;
  • Quality management and reliability;
  • Market risk control in supply chain finance;
  • Evaluation of manufacturing system productivity;
  • Personnel performance and reliability analysis;
  • Healthcare decision support system.

Manuscript Submission Information

Manuscripts should be submitted online at https://www.editorialmanager.com/ijfs/default.aspx.

Please select the designated special issue (SI) in the additional information Questionnaire (the fourth step).

A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.


Deadline for manuscript submissions: 31 December 2020
Notification of acceptance:  31 March 2021
Publication Date: June 2021