Optimization of Inventory Routing Problem in Refined Oil Logistics with the Perspective of Carbon Tax

In order to solve the optimization problem of the refined oil distribution system from the perspectives of low-carbon and environmental protection, this paper focuses on the characteristics of the secondary distribution of refined oil and combines it with the integrated optimization concept of refined oil distribution network, where a low-carbon inventory routing problem (LCIRP) model is constructed with the minimum total costs as the objective function on the basis of considering carbon emissions. An adaptive genetic algorithm combined with greedy algorithm is designed to solve the model, and an example is given to verify the effectiveness of the algorithm. Then, this paper solves the model with two parts by introducing a practical numerical example: in the first part, the LCIRP models with different carbon tax values are solved, which verifies the effectiveness of the model and proves that carbon tax policies can effectively reduce the carbon emissions in the secondary distribution network of refined oil; in the second part, the LCIRP models with the different maximum load capacity of oil tank trucks are solved, which provides the economic and environmentally friendly distribution schemes for refined oil distribution enterprises under the premise of carbon tax policies and load limitation. Finally, the emission reduction proposals that take into account both economic and environmental benefits are given respectively from the aspect of government environmental protection agencies and from the aspect of refined oil distribution enterprises.

[1]  Drazen Popovic,et al.  Variable Neighborhood Search heuristic for the Inventory Routing Problem in fuel delivery , 2012, Expert Syst. Appl..

[2]  Guohe Huang,et al.  A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty , 2011 .

[3]  Marius M. Solomon,et al.  Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints , 1987, Oper. Res..

[4]  Zhu Dao-li Interactively solving the vehicle routing problem for petroleum delivery , 2009 .

[5]  Li Mi Vehicle routing problem with time windows of petroleum products distribution based on order neighborhood system , 2015 .

[6]  Wen-Hsien Tsai,et al.  Integrating information about the cost of carbon through activity-based costing , 2012 .

[7]  Awi Federgruen,et al.  A Combined Vehicle Routing and Inventory Allocation Problem , 1984, Oper. Res..

[8]  Yi-Ming Wei,et al.  Chinese CO2 emission flows have reversed since the global financial crisis , 2017, Nature Communications.

[9]  Samir Elhedhli,et al.  Green supply chain network design to reduce carbon emissions , 2012 .

[10]  Shoudong Huang,et al.  A new crossover approach for solving the multiple travelling salesmen problem using genetic algorithms , 2013, Eur. J. Oper. Res..

[11]  Jacques Renaud,et al.  Trip packing in petrol stations replenishment , 2011 .

[12]  Yi-Ming Wei,et al.  Pattern changes in determinants of Chinese emissions , 2017 .

[13]  Pasquale Avella,et al.  Solving a fuel delivery problem by heuristic and exact approaches , 2004, Eur. J. Oper. Res..

[14]  Chun-Cheng Lin,et al.  Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths , 2014 .

[15]  Yu Ying-yin Improved genetic algorithm for solving TSP , 2014 .

[16]  Gilbert Laporte,et al.  A heuristic for the multi-period petrol station replenishment problem , 2008, Eur. J. Oper. Res..

[17]  Jacques Renaud,et al.  Production , Manufacturing and Logistics Heuristics for the multi-depot petrol station replenishment problem with time windows , 2012 .

[18]  J. Geunes,et al.  Analyzing the impacts of carbon regulatory mechanisms on supplier and mode selection decisions: An application to a biofuel supply chain , 2014 .

[19]  Lalit M. Patnaik,et al.  Adaptive probabilities of crossover and mutation in genetic algorithms , 1994, IEEE Trans. Syst. Man Cybern..

[20]  Fengming Tao,et al.  Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint , 2018, International journal of environmental research and public health.

[21]  Sun Xiao-yan Dispatching Optimization Model of Second Distribution of Gasolin & Diesel Oil and Solution Based on Genetic Algorithm , 2010 .

[22]  C. McAusland,et al.  Carbon Footprint Taxes , 2015 .

[23]  Yu Zhou,et al.  Influencing Factors and Decoupling Elasticity of China’s Transportation Carbon Emissions , 2018 .

[24]  Fengming Tao,et al.  Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax , 2017 .

[25]  Xiaofan Lai,et al.  A multi-objective optimization for green supply chain network design , 2011, Decis. Support Syst..

[26]  Tal Shima,et al.  Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms , 2006, Comput. Oper. Res..

[27]  M. Jaber,et al.  Supply chain coordination with emissions reduction incentives , 2013 .

[28]  Michel Gendreau,et al.  A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows , 2013, Comput. Oper. Res..

[29]  Wen-Hsien Tsai,et al.  A mixed activity-based costing decision model for green airline fleet planning under the constraints of the European Union Emissions Trading Scheme , 2012 .

[30]  Yi-Ming Wei,et al.  Consumption-based emission accounting for Chinese cities , 2016 .

[31]  Mitsuo Gen,et al.  An adaptive genetic algorithm for the time dependent inventory routing problem , 2014, J. Intell. Manuf..

[32]  de Ag Ton Kok,et al.  Analysis of Travel Times and CO2 Emissions in Time‐Dependent Vehicle Routing , 2012 .

[33]  Feng Zhen Multi-period vehicle routing problem with recurring dynamic time windows , 2011, ICSSSM11.

[34]  Bruce L. Golden,et al.  Analysis of a large scale vehicle routing problem with an inventory component , 1984 .

[35]  Gilbert Laporte,et al.  The petrol station replenishment problem with time windows , 2009, Comput. Oper. Res..