A Multiple Objective Model for Vehicle Routing Problem with Time Windows: A Case Study

2019 ◽  
Vol 889 ◽  
pp. 588-596
Author(s):  
Ho Thi Thu Ai ◽  
Nguyen Truong Thi ◽  
Nguyen Van Can
Keyword(s):  
Supply Chain ◽  
Vehicle Routing ◽  
Time Windows ◽  
Multiple Objective ◽  
Positive Contribution ◽  
Sustainable Supply Chain ◽  
Routing Problem ◽  
Environmental Objectives ◽  
Objective Model

Green transportation has emerged as an efficient way to promote a sustainable supply chain. Transportation activities have significant impact on the whole supply chain at any decision levels. At an operational level, vehicle routing decisions are one of the most critical determinants of the release of transportation emissions. Therefore, this study develops a mathematical model, with an aim to construct routes that simultaneously minimize total cost and total CO2emissions from the transportation activities of a case study located in Can Tho City, Vietnam. A multiple-objective model with the consideration of different vehicle loading capacity, and time windows is then solved using a Weighted Tchebycheff method. Results show that route selection has a positive contribution toward a better balance between economic and environmental objectives.

Network Mode Optimization for the DHL Supply Chain

2021 ◽  
Author(s):  
Yibo Dang ◽  
Manjeet Singh ◽  
Theodore T. Allen
Keyword(s):  
Supply Chain ◽  
Vehicle Routing ◽  
Time Windows ◽  
Cost Savings ◽  
Single Type ◽  
Planning Problem ◽  
Routing Problem ◽  
Time Restrictions ◽  
Driving Time ◽  
Using Data

DHL Supply Chain North America moves more than 20 million packages each year. DHL transportation planners perform routing and cost-deduction tasks for many business projects. We refer to the associated planning problem as the Vehicle Routing Problem with Time Regulations and Common Carriers (VRPTRCC). Unlike ordinary vehicle routing problems, which use only a single type of transportation mode, our VRPTRCC applications include make–buy decisions because some of the package deliveries are ultimately subcontracted to organizations other than DHL. Time regulation means that the problem considers not only delivery-time windows, but also layover and driving-time restrictions. Our developed Network Mode Optimization Tool (NMOT) is an ant-colony optimization (ACO)-based program that aids DHL Supply Chain transportation analysts in identifying cost savings in the ground logistic network. By using the NMOT, DHL and its customers have saved millions of dollars annually. Also, the NMOT is helping DHL to win new customers against bidding competitors and reducing estimation times from multiple weeks to hours. The results show an actual increase in profits compared with the previous process by more than 15% through a combination of new projects enabled and reduced current operational costs. The NMOT is implemented and evaluated by using data from ongoing projects.

scholarly journals Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: A case study

2019 ◽  
Vol 37 (1_suppl) ◽  
pp. 4-13 ◽  
Author(s):  
Erfan Babaee Tirkolaee ◽  
Parvin Abbasian ◽  
Mehdi Soltani ◽  
Seyed Ali Ghaffarian
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Computational Time ◽  
Waste Collection ◽  
Urban Waste ◽  
Routing Problem ◽  
Great Performance ◽  
Hard Problems

This paper studies a multi-trip vehicle routing problem with time windows specifically related to urban waste collection. Urban waste collection is one of the municipal activities with large costs and has many practical difficulties. In other words, waste collection and disposal is a costly task due to high operating expenses (fuel, maintenance, recycling, manpower, etc.) and small improvements in this field can result in tremendous savings on municipal expenditure. In the raised problem, the goal is to minimize total cost including traversing cost, vehicle employment cost, and exit penalty from permissible time windows. In this problem, the waste is deposited at the points indicating the demand nodes, in which each demand shows the volume of generated waste. Considering multiple trips for vehicles and time windows are the most critical features of the problem, so that the priorities of serving some specific places such as hospitals can be observed. Since vehicle routing problems (VRP) belongs to NP-hard problems, an efficient simulated annealing (SA) is proposed to solve the problem. The computational results show that our proposed algorithm has a great performance in a short computational time in comparison with the CPLEX solver. Finally, in order to demonstrate the applicability of the model, a case study is analyzed in Iran, and the optimal policies are presented.

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