2022 Vol.5 Jun.No2

• Title: Location planning of ship logistics distribution center considering time window
• Name: Thomas Michely
• Company: California American University,USA
• Abstract:

  Because the present method does not consider the distribution time constraint, it has the problem that the total cost of ship logistics distribution center is high, so it puts forward the method of site selection planning of ship logistics distribution center with time window. Based on bi-level programming theory to build the ship logistics distribution center location two-layer model, and calculate the model expression, and on this basis, the time window restraint, punishing function distribution, through genetic algorithm shipping logistics distribution center location two-layer model, model to the overall optimal solution, so as to realize the planning of logistics distribution center location of the ship. The experimental example includes 2 port cargo yards, 5 ship logistics distribution centers and 4 customer demand locations. The experimental results show that, compared with the existing methods, the total cost of the proposed method distribution center is lower under the condition of the same customer demand, which fully indicates that the proposed method has better planning effect.

  
  

• Keyword: Time window; Logistics; Distribution center; The location;
• DOI: 10.12250/jpciams2022090110
• Citation form: Thomas Michely.Location planning of ship logistics distribution center considering time window [J]. Computer Informatization and Mechanical System,2022,Vol.5,pp.55-57

[1] Li Xiaoping, Zhu Bingxu. Location Planning of Ship Steel Distribution Center Considering Time Window[J]. Industrial Engineering and Management, 2018, 23(5):156-161.

[2] Liu Yinying. Study on the Location-Routing Problem with Multiple Time Windows and Multiple Distribution Centers[J]. Public Utilities, 2020, 7(3):65-69.

[3] Jiang Zhenfeng, Chen Dongxu, Yang Zhongzhen, et al. Scheduling optimization of tramp shipping based on temporal and spatial attributes of shipping demand[J]. Journal of Traffic and Transportation Engineering, 2019, 19(3):157-165.

[4] Sun Molin, Zheng Zhongyi. Prediction of Vessel Traffic Accident Rate Based on Time Window Selection and SVR[J]. Navigation of China, 2019, 42 (1): 47-51.