Li Xinguang, Zhou Kang
School of Mechanical and Automobile, Qingdao University of Technology, Qingdao, 266520, China.
Traffic School, Northeast Forestry University, Harbin, 150040, China.
Environ Sci Pollut Res Int. 2021 Feb 23. doi: 10.1007/s11356-021-12992-w.
The issues of food safety and environmental protection are attracting more and more attention. Everyday, a large number of cold chain products are delivered from suppliers to customers. The cold chain products require refrigeration equipment in delivery and should be delivered to customers as soon as possible. Therefore, the challenge of reducing carbon emission and improving the customer satisfaction should be solved. This study presents the impact of carbon emission, customer satisfaction, construction cost, and operation cost on the location of cold chain logistics distribution center. A multi-objective location model for cold chain logistics distribution center considering carbon emission is established. The carbon emission equivalent cost model considers the dynamic carbon emission during transportation and the static carbon emission of the distribution center. The penalty cost under the time window is introduced into the penalty cost model of customer satisfaction, which represents a multi-objective mixed-integer linear programming problem. A non-dominated sorting genetic algorithm II (NSGA-II) is used to design the program through double-layer composite coding. NSGA-II uses a fast non-dominated sorting approach to reduce the computational complexity of non-dominated sorting. This algorithm uses the elitist control strategy, which does not need to share parameters and is more efficient in the multi-objective optimization process. The numerical results show that the proposed algorithm can generate appropriate Pareto solutions for all objectives.
食品安全和环境保护问题正吸引着越来越多的关注。每天,大量冷链产品从供应商交付给客户。冷链产品在运输过程中需要制冷设备,并且应尽快交付给客户。因此,需要解决减少碳排放和提高客户满意度的挑战。本研究提出了碳排放、客户满意度、建设成本和运营成本对冷链物流配送中心选址的影响。建立了考虑碳排放的冷链物流配送中心多目标选址模型。碳排放当量成本模型考虑了运输过程中的动态碳排放和配送中心的静态碳排放。将时间窗下的惩罚成本引入客户满意度惩罚成本模型,该模型代表一个多目标混合整数线性规划问题。采用非支配排序遗传算法II(NSGA-II)通过双层复合编码来设计方案。NSGA-II采用快速非支配排序方法来降低非支配排序的计算复杂度。该算法采用精英控制策略,无需共享参数,在多目标优化过程中效率更高。数值结果表明,所提算法能够为所有目标生成合适的帕累托解。