Dynamic Multicompartment Refrigerated Vehicle Routing Problem with Multigraph Based on Real-Time Traffic Information

Hou, Dengkai; Fan, Houming; Lv, Yingchun; Ren, Xiaoxue

doi:10.1155/2022/5538113

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…The simulation of traffic problems mainly requires real data. For example, Deng-Kai Hou et al [22] have applied real traffic data with the help of a two-stage mathematical model and heuristic algorithm and extracted useful results in their research. Dongxu Chen et al [23] have simulated the traffic balance of cars in VRP.…”

Section: Literature Reviewmentioning

confidence: 99%

Transportation Multi depot vehicle routing problem with optional transshipment demands

Akbari

Ghomi

2023

Preprint

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One of the important issues of transportation and delivery of goods is vehicle routing. These days, transportation issues are faced by many challenges, such as electric cars, a variety of products and services. This paper aims to reduce travel distance. To do this a mixed integer linear programming model is developed. It utilizes the vehicle routing problem with an optional transshipment model for single-product problems with one and two depots in small and non-small dimensions. In addition, parameters of customer demand are studied as stochastic with normal distribution. The situation of real-world condition has been obtained in the paper and a case study in Iran is given. Also, sensitivity analysis is made on some parameters. Numerical results indicate that the proposed model is relatively effective. Ultimately, some management insights are provided.

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Section: Literature Reviewmentioning

confidence: 99%

Transportation Multi depot vehicle routing problem with optional transshipment demands

Akbari

Ghomi

2023

Preprint

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“…This is achieved through three steps: vehicle speed or traffic flow prediction, rolling optimization, and feedback. In [28] and [29], the characteristics of the industry are considered, and route planning models are designed for different applications. In [28], the focus is on real-time route planning and adjustment for refrigerated trucks based on preoptimization, while [29] proposes a route planning optimization method for evacuation and rescue scenarios considering the unpredictability and dynamic nature of traffic states during these situations.…”

Section: Route Planning For Sustainable Mobilitymentioning

confidence: 99%

Drive on a Greener Way: A Case Study on Navigating Cross-Regional Traffic Networks in South China

Zhang,

Zhou,

Wang

et al. 2023

Applied Sciences

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Green navigation presents a challenge to sustainable mobility. Carbon emissions are a key indicator for evaluating the sustainability of a route. Some methods of green navigation consider the fastest and shortest route to be the least carbon-emitting option, solely from the driver’s perspective. To address this issue, various studies have incorporated road factors into the sustainability evaluation model and designed static route planning algorithms to minimize carbon emissions. However, there has been no comprehensive analysis of carbon emissions from both the road and the driver perspectives, and the influence of a sustainability evaluation using dynamic traffic states has not been considered. In this paper, we propose a carbon emission evaluation model based on the life cycle assessment (LCA) and a dynamic route planning algorithm that focuses on near-real-time traffic states. First, we develop an evaluation model for carbon emissions from both the road and the driver perspectives using a carbon footprint measurement method. Next, we propose a route planning method with both a static calculation and near-real-time adjustment to minimize carbon emissions. Finally, we select three cases from South China with different characteristics to verify the effectiveness of our model and algorithm. This evaluation model calculates the carbon emissions caused by all parties involved, providing a comprehensive assessment of the total carbon emissions generated by traffic. This approach addresses the problem of traditional route planning, which often fails to account for the influences of variable traffic conditions on the greenest route. We verify the effectiveness of the greenest navigation algorithm and near-real-time green navigation and apply these two aspects to cases where the greenest route is compared with other common navigation results from different dimensions. We compare carbon emissions from vehicles and roads from electric vehicles and gasoline-powered vehicles. If an electric vehicle is equipped with a wind power generator, the proportion of the vehicle’s carbon emissions will be very small. For other vehicle types, the carbon emissions will be more than 1000 times the road emissions.

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“…Martins et al [14] solved a multi-period setting problem in terms of product complexity. Hou et al [15] addressed routing problems with real-time traffic information. Golestani et al [16] solved the hub location problem using MTJD.…”

Section: Literature Reviewmentioning

confidence: 99%

“…[14] Addressing the time window allocation problem for product complexity. [15] Based on real-time traffic information to solve the dynamic multi-compartment VRP. [16] Jointly optimized hub location and MTJD for the perishable product supply chain.…”

Section: Vrptw Under Mtjd [11]mentioning

confidence: 99%

See 1 more Smart Citation

Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail

Zhan

Jiang

2022

Sustainability

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Community retail is an important research issue in the field of fresh agriproduct e-commerce. This paper focuses on the problem of last-mile multi-temperature joint distribution (MTJD), which combines time coupling, order allocation, and vehicle scheduling. Firstly, according to the temperature of a refrigerated truck in multi-temperature zones, a split-order packing decision is proposed to integrate the different types of fresh agriproduct. Then, the order allocation strategy is incorporated into a comprehensive picking and distribution schedule, while taking into account the time-coupling of picking, distribution, and delivery time limit. To improve consumer satisfaction and reduce order fulfillment costs, an optimization model combining multi-item order allocation and vehicle scheduling is established, to determine the optimal order allocation scheme and distribution route. Finally, taking fresh agriproduct community retail in the Gulou District of Nanjing as an example, the effectiveness and feasibility of the model are illustrated. The numerical results of medium- to large-scale examples show that, compared with the variable neighborhood search algorithm (VNS) and genetic algorithm (GA), the mixed genetic algorithm (MGA) can save 29% of CPU time and 65% of iterations. This study considers the integrated optimization of multiple links, to provide scientific decision support for fresh agriproduct e-commerce enterprises.

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Dynamic Multicompartment Refrigerated Vehicle Routing Problem with Multigraph Based on Real-Time Traffic Information

Cited by 6 publications

References 21 publications

Transportation Multi depot vehicle routing problem with optional transshipment demands

Transportation Multi depot vehicle routing problem with optional transshipment demands

Drive on a Greener Way: A Case Study on Navigating Cross-Regional Traffic Networks in South China

Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail

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