Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax

被引:111
作者
Wang, Songyi [1 ]
Tao, Fengming [1 ]
Shi, Yuhe [2 ]
Wen, Haolin [3 ]
机构
[1] Chongqing Univ, Coll Mech Engn, Chongqing 400044, Peoples R China
[2] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu 610031, Peoples R China
[3] Naval Univ Engn, Dept Management Engn, Wuhan 430033, Peoples R China
基金
中国国家自然科学基金;
关键词
cold-chain logistic distribution; vehicle routing problem; cycle evolutionary genetic algorithm; carbon tax; carbon footprint; FOOTPRINT; ALGORITHM;
D O I
10.3390/su9050694
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In order to reduce the cost pressure on cold-chain logistics brought by the carbon tax policy, this paper investigates optimization of Vehicle Routing Problem (VRP) with time windows for cold-chain logistics based on carbon tax in China. Then, a green and low-carbon cold chain logistics distribution route optimization model with minimum cost is constructed. Taking the lowest cost as the objective function, the total cost of distribution includes the following costs: the fixed costs which generate in distribution process of vehicle, transportation costs, damage costs, refrigeration costs, penalty costs, shortage costs and carbon emission costs. This paper further proposes a Cycle Evolutionary Genetic Algorithm (CEGA) to solve the model. Meanwhile, actual data are used with CEGA to carry out numerical experiments in order to discuss changes of distribution routes with different carbon emissions under different carbon taxes and their influence on the total distribution cost. The critical carbon tax value of carbon emissions and distribution cost is obtained through experimental analysis. The research results of this paper provide effective advice, which is not only for the government on carbon tax decision, but also for the logistics companies on controlling carbon emissions during distribution.
引用
收藏
页数:23
相关论文
共 44 条
  • [1] A rich vehicle routing problem dealing with perishable food: a case study
    Amorim, Pedro
    Parragh, Sophie N.
    Sperandio, Fabricio
    Almada-Lobo, Bernardo
    [J]. TOP, 2014, 22 (02) : 489 - 508
  • [2] Best-order crossover for permutation-based evolutionary algorithms
    Andreica, Anca
    Chira, Camelia
    [J]. APPLIED INTELLIGENCE, 2015, 42 (04) : 751 - 776
  • [3] [Anonymous], 2016, MATH PRACTICE THEORY
  • [4] International mobility in carbon dioxide emissions
    Antonio Duro, Juan
    [J]. ENERGY POLICY, 2013, 55 : 208 - 216
  • [5] Bermudez C., 2010, IBEROAM J INTEL ARTI, V14, P34
  • [6] Vehicle routing problems with multiple trips
    Cattaruzza, Diego
    Absi, Nabil
    Feillet, Dominique
    [J]. 4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH, 2016, 14 (03): : 223 - 259
  • [7] THE TRUCK DISPATCHING PROBLEM
    DANTZIG, GB
    RAMSER, JH
    [J]. MANAGEMENT SCIENCE, 1959, 6 (01) : 80 - 91
  • [8] A NEW HEURISTIC FOR THE FLEET SIZE AND MIX VEHICLE-ROUTING PROBLEM
    DESROCHERS, M
    VERHOOG, TW
    [J]. COMPUTERS & OPERATIONS RESEARCH, 1991, 18 (03) : 263 - 274
  • [9] Self-imposed time windows in vehicle routing problems
    Jabali, Ola
    Leus, Roel
    Van Woensel, Tom
    de Kok, Ton
    [J]. OR SPECTRUM, 2015, 37 (02) : 331 - 352
  • [10] Ji Y., 2015, P INT C MOD SIM APPL