scholarly journals Collaboration and Resource Sharing in the Multidepot Multiperiod Vehicle Routing Problem with Pickups and Deliveries

2020 ◽  
Vol 12 (15) ◽  
pp. 5966
Author(s):  
Yong Wang ◽  
Qin Li ◽  
Xiangyang Guan ◽  
Jianxin Fan ◽  
Yong Liu ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Resource Utilization ◽  
Heuristic Algorithm ◽  
Vehicle Routing Problem ◽  
Resource Sharing ◽  
Pickup And Delivery ◽  
Routing Problem ◽  
Hybrid Heuristic ◽  
Operational Costs ◽  
Hybrid Heuristic Algorithm

In this work, a multidepot multiperiod vehicle routing problem with pickups and deliveries (MDPVRPPD) is solved by optimizing logistics networks with collaboration and resource sharing among logistics service providers. The optimal solution can satisfy customer demands with periodic time characteristics and incorporate pickup and delivery services with maximum resource utilization. A collaborative mechanism is developed to rearrange both the open and closed vehicle routes among multiple pickup and delivery centers with improved transportation efficiency and reduced operational costs. The effects of resource sharing strategies combining customer information sharing, facility service sharing, and vehicle sharing are investigated across multiple service periods to maximize resource utilization and refine the resource configuration. A multiobjective optimization model is developed to formulate the MDPVRPPD so that the minimum total operational costs, waiting time, and the number of vehicles are obtained. A hybrid heuristic algorithm incorporating a 3D clustering and an improved multiobjective particle swarm optimization (IMOPSO) algorithm is introduced to solve the MDPVRPPD and find Pareto optimal solutions. The proposed hybrid heuristic algorithm is based on a selective exchange mechanism that enhances local and global searching capabilities. Results demonstrate that the proposed IMOPSO outperforms other existing algorithms. We also study profit allocation issues to quantify the stability and sustainability of long-term collaboration among logistics participants, using the minimum costs remaining savings method. The proposed model and solution methods are validated by conducting an empirical study of a real system in Chongqing City, China. This study contributes to the development of efficient urban logistics distribution systems, and facilitates the expansion of intelligent and sustainable supply chains.

scholarly journals Optimization of Vehicle Routing with Pickup Based on Multibatch Production

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Hongtao Hu ◽  
Jiao Mo ◽  
Chengle Ma
Keyword(s):  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Programming Model ◽  
Raw Materials ◽  
Pso Algorithm ◽  
Mixed Integer ◽  
Two Stage ◽  
Routing Problem ◽  
Hybrid Heuristic ◽  
Hybrid Heuristic Algorithm

To reduce the inventory cost and ensure product quality while meeting the diverse demands of customers, manufacturers yield products in batches. However, the raw materials required for manufacturing need to be obtained from suppliers in advance, making it necessary to understand beforehand how to best structure the pickup routes so as to reduce the cost of picking up and stocking while also ensuring the supply of raw materials required for each batch of production. To reduce the transportation and inventory costs, therefore, this paper establishes a mixed integer programming model for the joint optimization of multibatch production and vehicle routing problems involving a pickup. Following this, a two-stage hybrid heuristic algorithm is proposed to solve this model. In the first stage, an integrated algorithm, combining the Clarke-Wright (CW) algorithm and the Record to Record (RTR) travel algorithm, was used to solve vehicle routing problem. In the second stage, the Particle Swarm Optimization (PSO) algorithm was used to allocate vehicles to each production batch. Multiple sets of numerical experiments were then performed to validate the effectiveness of the proposed model and the performance efficiency of the two-stage hybrid heuristic algorithm.

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