Location Optimization Model of Logistics Distribution Center for Agricultural Products

2018 ◽  
Author(s):  
Yu Wu
Keyword(s):  
Optimization Model ◽  
Distribution Center ◽  
Agricultural Products ◽  
Location Optimization ◽  
Logistics Distribution

scholarly journals Location Optimization Model of Regional Express Distribution Center

2013 ◽  
Vol 96 ◽  
pp. 1008-1013 ◽  
Author(s):  
Yingfeng Ji ◽  
Hualong Yang ◽  
Yan Zhang ◽  
Weixin Zhong
Keyword(s):  
Optimization Model ◽  
Distribution Center ◽  
Location Optimization

scholarly journals A Study on Location-Route Optimization Model of Logistics Distribution Center and Its Heuristics Solving Algorithm in Multi-Modal Transport Network

2020 ◽  
Author(s):  
Hui Hu ◽  
Jianliang Li ◽  
Xudong Zhao
Keyword(s):  
Optimization Model ◽  
Large Scale ◽  
Optimal Solution ◽  
Objective Evaluation ◽  
Distribution Center ◽  
Transport Network ◽  
Route Optimization ◽  
Logistics Distribution ◽  
Multi Objective ◽  
Decision Variables

Taking environmental concerns into consideration, a logistics distribution center location-route multi-objective optimization model and its solving algorithm are studied in multi-modal transport network context. The objective functions in the model include total operation cost, delivery time and carbon emission goals. The model’s decision variables are product volumes with different transport modes and the constraints concerned with investment budget, limited capacity etc. Aimed at the model structure, a two-stage heuristic solving algorithm for single objective model is put forward and its validity is proved. On the basis of solutions which are searched by the heuristic solving algorithm, an optimal solution is obtained using one of multi-objective evaluation methods. Finally, a large scale multi-modal distribution network example is provided to illustrate feasibility and effectiveness of the model and the algorithm by comparing solving efficiency and results, and it finds a railway-based multi-modal transport network has the most competitive advantage.

Research on the Distribution Route Optimization of Agricultural Product Logistics Based on Particle Swarm

2013 ◽  
Vol 790 ◽  
pp. 690-696
Author(s):  
Jun Liu ◽  
Jun Xiang ◽  
Gui Lan Zou
Keyword(s):  
Optimization Model ◽  
Time Windows ◽  
Particle Swarm ◽  
Agricultural Products ◽  
Route Optimization ◽  
Agricultural Product ◽  
Swarm Optimization ◽  
Logistics Distribution ◽  
Optimum Model ◽  
The Cost

Through an analysis of the characteristics of the Agricultural Products Logistics and its influence on the vehicle scheduling, this paper is to describe the vehicle routes whose vehicle number is uncertain and which are with time windows, to establish a distribution route optimization model which is effected by the cost and has a time limitation, to solve the model with the Compound Optimum Model Particle Swarm Optimization, and to compare it through some case. The optimization model of Agricultural Products Logistics has good practical value on reduce the cost of agricultural products logistics and improve the efficiency of logistics distribution of agricultural products.

scholarly journals Research on vehicle scheduling based on C-W algorithm

2021 ◽  
Vol 2083 (3) ◽  
pp. 032009
Author(s):  
Meng Wang
Keyword(s):  
Center Of Gravity ◽  
Distribution Center ◽  
Transportation Costs ◽  
Agricultural Products ◽  
Vehicle Scheduling ◽  
Gravity Method ◽  
Logistics Distribution ◽  
Vehicle Route ◽  
Logistics Company ◽  
Saving Algorithm

Abstract Vehicle scheduling is one of the most important links in logistics distribution, a large number of demands also lead to logistics companies have to reasonably arrange the transportation of vehicle routes to save costs. By optimizing the distribution routes of vehicles, logistics companies can save transportation mileage and thus save transportation costs. In this paper,10 demand points of an agricultural products logistics company in Beijing are selected, and the location of the distribution center is obtained through the center of gravity method. Finally, the route allocation is completed by using the mileage saving algorithm, and the scheduling of transport vehicles is realized. The example shows that the mileage saving algorithm can optimize the vehicle route and realize route allocation.

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