Multi-Trip Time-Dependent Vehicle Routing Problem with Split Delivery

Zhang, Jie; Zhu, Yifan; Li, Xiaobo; Ming, Mengjun; Wang, Weiping; Wang, Tao

doi:10.3390/math10193527

Cited by 6 publications

(2 citation statements)

References 36 publications

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“…Recently, more and more researchers focus on variation VRPs, such as the VRP with time windows [5,6], the VRP with simultaneous delivery and pickup [7,8] and the VRP with heterogeneous fleet [9,10]. These VRPs come from reality and have high practical application values [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

An Improved Genetic Algorithm for the Granularity-Based Split Vehicle Routing Problem with Simultaneous Delivery and Pickup

Liu,

Qin,

Liu

2023

Mathematics

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The Split Vehicle Routing Problem with Simultaneous Delivery and Pickup (SVRPSDP) consists of two subproblems, i.e., the Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP) and the Split Delivery Vehicle Routing Problem (SDVRP). Compared to the subproblems, SVRPSDP is much closer to reality. However, some realistic factors are still ignored in SVRPSDP. For example, the shipments are integrated and cannot be infinitely subdivided. Hence, this paper investigates the Granularity-based Split Vehicle Routing Problem with Simultaneous Delivery and Pickup (GSVRPSDP). The characteristics of GSVRPSDP are that the demands of customers are split into individual shipments and both the volume and weight of each shipment are considered. In order to solve GSVRPSDP efficiently, a Genetic-Simulated hybrid algorithm (GA-SA) is proposed, in which Simulated Annealing (SA) is inserted into the Genetic Algorithm (GA) framework to improve the global search abilities of individuals. The experimental results indicate that GA-SA can achieve lower total costs of routes compared to the traditional meta-algorithms, such as GA, SA and Particle Swarm Optimization (PSO), with a reduction of more than 10%. In the further analysis, the space utilization and capacity utilization of vehicles are calculated, which achieve 86.1% and 88.9%, respectively. These values are much higher than those achieved by GA (71.2% and 74.8%, respectively) and PSO (60.9% and 65.7%, respectively), further confirming the effectiveness of GA-SA. And the superiority of simultaneous delivery and pickup is proved by comparing with separate delivery and pickup. Specifically, the costs of separate delivery and pickup are more than 80% higher than that of simultaneous delivery and pickup.

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Section: Introductionmentioning

confidence: 99%

An Improved Genetic Algorithm for the Granularity-Based Split Vehicle Routing Problem with Simultaneous Delivery and Pickup

Liu,

Qin,

Liu

2023

Mathematics

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“…With respect to the above, the most common variants of the vehicle-routing models are explained below [50][51][52][53][54][55][56]:…”

mentioning

confidence: 99%

A Routing Model for the Distribution of Perishable Food in a Green Cold Chain

Pérez-Lechuga,

Martínez-Sánchez,

Venegas-Martínez

et al. 2024

Mathematics

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In this research, we develop an extension of the stochastic routing model with a fixed capacity for the distribution of perishable products with a time window. We use theoretical probability distributions to model the life of transported products and travel times in the network. Our main objective is to maximize the probability of delivering products within the established deadline with a certain level of customer service. Our project is justified from the perspective of reducing the pollution caused by greenhouse gases generated in the process. To optimize the proposed model, we use a Generic Random Search Algorithm. Finally, we apply the idea to a real problem of designing strategies for the optimal management of perishable food distribution routes that involve a time window, the objective being to maximize the probability of meeting the time limit assigned to the route problem by reducing, in this way, the pollution generated by refrigerated transport.

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