A novel multi-criteria decision making method for assessing health-care waste treatment technologies based on D numbers

被引:164
作者
Xiao, Fuyuan [1 ]
机构
[1] Southwest Univ, Sch Comp & Informat Sci, 2 Tiansheng Rd, Chongqing 400715, Peoples R China
基金
中国国家自然科学基金;
关键词
Health-care waste (HCW); HCW management; HCW treatment technology; D numbers; Multi-criteria decision making; POWER AGGREGATION OPERATOR; DEPENDENCE ASSESSMENT; MEDICAL WASTE; FAILURE MODE; MANAGEMENT; HOSPITALS; SIMILARITY; DISPOSAL; SAFETY;
D O I
10.1016/j.engappai.2018.03.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Health-care waste (HCW) management is a complex problem influenced by many aspects, such as, economic, environment, technical, social, etc. A selection of the best treatment technology for HCW management can be regarded as a complex multi-criteria decision making problem where a number of alternatives and multiple evaluation criteria are need to be considered. In addition, decision makers often express their personal assessments by using multi-granularity linguistic term sets. Due to the involvement of human judgment, various uncertainties are introduced in the HCW process. One critical issue of the HCW treatment technology selection is the representation and handling of uncertain information. In response, a novel multi-criteria decision making method is proposed for the HCW treatment technology selection problem based on an effective representation model of uncertain information, called D numbers. In the proposal, the assessment results of HCW treatment are expressed and modeled by D numbers. It provides a new framework for the HCW treatment technology selection problem in which it was effective and feasible to handle MCDM problems under various uncertainties environment. Comparing with the existing method, the proposed method is clear and concise. Finally, an empirical case study in Shanghai, China is illustrated to validate the feasibility and applicability of the proposed method. As shown in the results, the proposed method selects steam sterilization as the optimal technology to deal with the health-care wastes which is consistent with the existing work where fewer pollutants are discharged and non-hazardous residues are produced so that it decreases more impacts on the environment and public health. The experimental results demonstrate that the proposed method can handle the HCW treatment technology selection problem effectively under complex and uncertain environments.
引用
收藏
页码:216 / 225
页数:10
相关论文
共 87 条
  • [11] Assessing future scenarios for health care waste management using a multi-criteria decision analysis tool: A case study in the Turkish West Black Sea Region
    Ciplak, Nesli
    [J]. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, 2015, 65 (08) : 919 - 929
  • [12] UPPER AND LOWER PROBABILITIES INDUCED BY A MULTIVALUED MAPPING
    DEMPSTER, AP
    [J]. ANNALS OF MATHEMATICAL STATISTICS, 1967, 38 (02): : 325 - &
  • [13] Deng X, 2018, SOFT COMPUT, P1
  • [14] An Evidential Axiomatic Design Approach for Decision Making Using the Evaluation of Belief Structure Satisfaction to Uncertain Target Values
    Deng, Xinyang
    Jiang, Wen
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2018, 33 (01) : 15 - 32
  • [15] An improved distance-based total uncertainty measure in belief function theory
    Deng, Xinyang
    Xiao, Fuyuan
    Deng, Yong
    [J]. APPLIED INTELLIGENCE, 2017, 46 (04) : 898 - 915
  • [16] Evidence Combination From an Evolutionary Game Theory Perspective
    Deng, Xinyang
    Han, Deqiang
    Dezert, Jean
    Deng, Yong
    Shyr, Yu
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (09) : 2070 - 2082
  • [17] Environmental impact assessment based on D numbers
    Deng, Xinyang
    Hu, Yong
    Deng, Yong
    Mahadevan, Sankaran
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (02) : 635 - 643
  • [18] Deng Y., 2012, J INFORM COMPUT SCI, V9, P2421
  • [19] A K-NEAREST NEIGHBOR CLASSIFICATION RULE-BASED ON DEMPSTER-SHAFER THEORY
    DENOEUX, T
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1995, 25 (05): : 804 - 813
  • [20] Adequate is better: particle swarm optimization with limited-information
    Du, Wen-Bo
    Gao, Yang
    Liu, Chen
    Zheng, Zheng
    Wang, Zhen
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2015, 268 : 832 - 838