Research on Vehicle Route Planning with Capacity Limitation Based on Adaptive Large-scale Neighborhood Search Algorithm

Author(s):  
Keyi Huang ◽  
Jiabin Ma ◽  
Xiaoyang Liu
Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1734
Author(s):  
Yanjun Shi ◽  
Lingling Lv ◽  
Hao Yu ◽  
Liangjie Yu ◽  
Zihui Zhang

Roadside Units Deployment (RSUD) is of great importance to smart transportation with the Internet of Things (IoT). It is believed to be not feasible for RSUD to cover and perceive the whole area due to the high installation and maintenance costs. The candidate locations set of RSUD may be huge for a future urban area with vehicle-to-everything (V2X) networks. Most of the previous studies tried to maximize the Roadside Units (RSU) coverage only and made few reports on emergency scenarios, such as accidents happening. We tried to find better candidate locations of RSUD in some grid road networks with equal length streets, and then chose some of these locations for final installation with a given budget to minimize the average reporting time of emergency messages in V2X networks. Firstly, we analyzed candidate locations of RSUD for different cases of RSUs and vehicles. Then we proposed a message dissemination model for RSUD with the V2X network, and a center-rule-based neighborhood search algorithm (CNSA for short). In this algorithm, we generated initial solutions with the center rule and then obtained better neighbor solutions. Numerical simulation results from small-scale urban streets showed that the proposed algorithm performs well on execution time. Simulation results with Veins and Simulation of Urban Mobility) (SUMO) verified the proposed model and CNSA for evaluating the RSUD scheme by distance instead of accident reporting time in urban areas with large-scale traffic flow.


2007 ◽  
Vol 19 (3) ◽  
pp. 416-428 ◽  
Author(s):  
Ravindra K. Ahuja ◽  
Jon Goodstein ◽  
Amit Mukherjee ◽  
James B. Orlin ◽  
Dushyant Sharma

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