Multi-objective solid transportation-location problem with variable carbon emission in inventory management: a hybrid approach

被引:83
作者
Das, Soumen Kumar [1 ]
Pervin, Magfura [1 ]
Roy, Sankar Kumar [1 ]
Weber, Gerhard Wilhelm [2 ,3 ]
机构
[1] Vidyasagar Univ, Dept Appl Math Oceanol & Comp Programming, Midnapore 721102, W Bengal, India
[2] Poznan Univ Tech, Fac Engn Management, Ul Strzelecka 11, PL-60965 Poznan, Poland
[3] Middle East Tech Univ, Inst Appl Math, TR-06800 Ankara, Turkey
关键词
Facility location problem; Solid transportation problem; Inventory management; Variable carbon emission; Hybrid approach; Multi-objective decision making; SUPPLY CHAIN NETWORK; FACILITY LOCATION; OPTIMIZATION; MODEL;
D O I
10.1007/s10479-020-03809-z
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The most important strategic issue for several industries is where to find facilities so as to discover a transportation path for optimizing the objectives at the same time. This paper acquaints a streamlining model with incorporate the facility location problem, solid transportation problem, and inventory management under multi-objective environment. The aims of the stated formulation are multi-fold: (i) to seek the optimum locations for potential facilities in Euclidean plane; (ii) to find the amount of distributed commodities; and (iii) to reduce the overall transportation cost, transportation time, and inventory cost along with the carbon emission cost. Here, variable carbon emission cost is taken into consideration because of the variable locations of facilities and the amount of distributed products. After that, a new hybrid approach is introduced dependent on an alternating locate-allocate heuristic and the intuitionistic fuzzy programming to get the Pareto-optimal solution of the proposed formulation. In fact, the performances of our findings are discussed with two numerical examples. Sensitivity analysis is executed to check the resiliency of the parameters. Ultimately, managerial insights, conclusions and avenues of future studies are offered at the end of this study.
引用
收藏
页码:283 / 309
页数:27
相关论文
共 48 条
  • [1] A facility location model for global closed-loop supply chain network design
    Amin, Saman Hassanzadeh
    Baki, Fazle
    [J]. APPLIED MATHEMATICAL MODELLING, 2017, 41 : 316 - 330
  • [2] INTUITIONISTIC FUZZY-SETS
    ATANASSOV, KT
    [J]. FUZZY SETS AND SYSTEMS, 1986, 20 (01) : 87 - 96
  • [3] Transportation-location problem with unknown number of facilities
    Carlo, Hector J.
    David, Victor
    Salvat-Davila, Gabriela S.
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 112 : 212 - 220
  • [4] The location-allocation problem of drone base stations
    Cicek, Cihan Tugrul
    Gultekin, Hakan
    Tavli, Bulent
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2019, 111 : 155 - 176
  • [5] TRANSPORTATION-LOCATION PROBLEM
    COOPER, L
    [J]. OPERATIONS RESEARCH, 1972, 20 (01) : 94 - &
  • [6] HEURISTIC METHODS FOR LOCATION-ALLOCATION PROBLEMS .1. INTRODUCTION
    COOPER, L
    [J]. SIAM REVIEW, 1964, 6 (01) : 37 - &
  • [7] Application of Type-2 Fuzzy Logic to a Multiobjective Green Solid Transportation-Location Problem With Dwell Time Under Carbon Tax, Cap, and Offset Policy: Fuzzy Versus Nonfuzzy Techniques
    Das, Soumen Kumar
    Roy, Sankar Kumar
    Weber, Gerhard-Wilhelm
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 28 (11) : 2711 - 2725
  • [8] An exact and a heuristic approach for the transportation-p-facility location problem
    Das, Soumen Kumar
    Roy, Sankar Kumar
    Weber, Gerhard Wilhelm
    [J]. COMPUTATIONAL MANAGEMENT SCIENCE, 2020, 17 (03) : 389 - 407
  • [9] Heuristic approaches for solid transportation-p-facility location problem
    Das, Soumen Kumar
    Roy, Sankar Kumar
    Weber, Gerhard Wilhelm
    [J]. CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH, 2020, 28 (03) : 939 - 961
  • [10] Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment
    Das, Soumen Kumar
    Roy, Sankar Kumar
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 132 : 311 - 324