CLUSTERING ALGORITHM FOR A VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

被引:2
|
作者
Thi Diem Chau Le [1 ,2 ]
Duc Duy Nguyen [3 ]
Olah, Judit [1 ,4 ]
Pakurar, Miklos [1 ]
机构
[1] Univ Debrecen, Fac Econ & Business, Debrecen, Hungary
[2] Ho Chi Minh City Univ Technol VNUHCM, Dept Qual Assurance, Ho Chi Minh City, Vietnam
[3] LUT Univ, Sch Business & Management, Lappeenranta, Finland
[4] Univ Johannesburg, Coll Business & Econ, Dept Publ Management & Governance, Johannesburg, South Africa
关键词
vehicle routing problem; logistics; time window; cluster; route; k-means clustering; transportation;
D O I
10.3846/transport.2022.16850
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The demand for daily food purchases has increased dramatically, especially during the Covid-19 pandemic. This requires suppliers to face a huge and complex problem of delivering products that meet the needs of their customers on a daily basis. It also puts great pressure on managers on how to make day-to-day decisions quickly and efficiently to both satisfy customer requirements and satisfy capacity constraints. This study proposes a combination of the cluster-first ??? route-second method and k-means clustering algorithm to deal with a large Vehicle Routing Problem with Time Windows (VRPTW) in the logistics and transportation field. The purpose of this research is to assist decision-makers to make quick and efficient decisions, based on optimal costs, the number of vehicles, delivery time, and truck capacity efficiency. A distribution system of perishable goods in Vietnam is used as a case study to illustrate the effectiveness of our mathematical model. In particular, perishable goods include fresh products of fish, chicken, beef, and pork. These products are packed in different sizes and transferred by vehicles with 1000 kg capacity. Besides, they are delivered from a depot to the main 39 customers of the company with arrival times following customers??? time window. All of the data are collected from a logistics company in Ho Chi Minh city (Vietnam). The result shows that the application of the clustering algorithm reduces the time for finding the optimal solutions. Especially, it only takes an average of 0.36 s to provide an optimal solution to a large Vehicle Routing Problem (VRP) with 39 nodes. In addition, the number of trucks, their operating costs, and their utilization are also shown fully. The logistics company needs 11 trucks to deliver their products to 39 customers. The utilization of each truck is more than 70%. This operation takes the total costs of 6586215.32 VND (Vietnamese Dong), of which, the transportation cost is 1086215.32 VND. This research mainly contributes an effective method for enterprises to quickly find the optimal solution to the problem of product supply.
引用
收藏
页码:17 / 27
页数:11
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