Multiple Group Decision Making for Selecting Emergency Alternatives: A Novel Method Based on the LDWPA Operator and LD-MABAC.

Journal: International journal of environmental research and public health
Published Date:

Abstract

When an emergency event occurs, it is critical to respond in the shortest possible time. Therefore, the rationality and effectiveness of emergency decisions are the key links in emergency management. In this paper, with aims to investigate the problem of emergency alternatives selection, in which a large number of experts from multiple groups consider the linguistic evaluations of emergency alternatives and prior orders of criteria, a novel emergency decision method is proposed. First, many experts from multiple subgroups are employed to evaluate the emergency alternatives associated with multiple criteria in the format of linguistic terms. Then, linguistic distribution evaluations for the emergency alternatives of the criteria associated with each subgroup are constructed. With respect to the linguistic distribution evaluations associated with the different subgroups, the linguistic distribution power average (LDPA) and linguistic distribution weighted power average (LDWPA) operators are developed so as to aggregate the subgroups' evaluations. Next, based on the linguistic distribution multi-attributive border approximation area comparison (LD-MABAC) method, the distance matrix of the emergency alternatives is calculated. Furthermore, the prior weights of the criteria are determined based on the distance values. Finally, the ranking result of the emergency alternatives is derived. A practical example of emergency alternatives selection is adopted to illustrate the availability and practicability of the proposed method.

Authors

  • Xia Liang
    School of Agriculture, Food and Ecosystem Sciences, Faculty of Science, The University of Melbourne, Parkville, VIC 3010, Australia.
  • Fei Teng
    State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center Chengdu 610041 China yuluot@scu.edu.cn.
  • Yan Sun
    Department of Biochemistry, Albert Einstein College of Medicine, New York, NY, United States.