题名 | Benchmarking Dynamic Capacitated Arc Routing Algorithms Using Real-World Traffic Simulation |
作者 | |
通讯作者 | Yao,Xin |
DOI | |
发表日期 | 2022
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会议录名称 | |
摘要 | The dynamic capacitated arc routing problem (DCARP) aims at re-scheduling the service plans of agents, such as vehicles in a city scenario, when dynamic events deteriorate the quality of the current schedule. Various algorithms have been proposed to solve DCARP instances in different dynamic scenarios. However, most existing work evaluated their algorithms' performance based on artificially constructed dynamic environments instead of using more realistic traffic simulations which are built on actual traffic data. In this paper, we constructed a novel DCARP benchmarking framework based on the Simulation of Urban MObility (SUMO) transportation simulation software, which allows to include real-world traffic environments for generating a set of DCARP instances from dynamic events, such as road congestion or task changes. The flexibility of the framework allows to develop DCARP optimization algorithms and evaluate their effectiveness more comprehensively. We use the benchmarking framework to generate 12 different dynamic instances using real-world traffic data of Dublin City. We then demonstrate the value of our framework by using these instances to compare our previously proposed hybrid local search algorithm (HyLS) with a state-of-the-art meta-heuristic optimization algorithm. The generated benchmark scenarios indicate that HyLS is a very effective optimizer on DCARP scenarios with real traffic data for reducing the total service cost. They also demonstrate the importance of our DCARP benchmarking framework for the development and benchmarking of optimization algorithms in more realistic scenarios. |
关键词 | |
学校署名 | 通讯
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语种 | 英语
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相关链接 | [Scopus记录] |
Scopus记录号 | 2-s2.0-85138717817
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来源库 | Scopus
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引用统计 |
被引频次[WOS]:0
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成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/402759 |
专题 | 工学院_计算机科学与工程系 工学院_斯发基斯可信自主研究院 |
作者单位 | 1.School of Computer Science,University of Birmingham,Birmingham,United Kingdom 2.Honda Research Institute Europe GmbH,Offenbach,Germany 3.SUSTech,Department of Computer Science and Engineering,Shenzhen,China 4.Research Institute of Trustworthy Autonomous Systems (RITAS),SUSTech,China 5.SUSTech,Guangdong Key Laboratory of Brain-inspired Intelligent Computation,China |
通讯作者单位 | 计算机科学与工程系; 斯发基斯可信自主系统研究院; 南方科技大学 |
推荐引用方式 GB/T 7714 |
Tong,Hao,Minku,Leandro L.,Menzel,Stefan,et al. Benchmarking Dynamic Capacitated Arc Routing Algorithms Using Real-World Traffic Simulation[C],2022.
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条目包含的文件 | 条目无相关文件。 |
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