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Mitigating Traffic Congestion:Solving the Ride-Matching Problem by Bee Colony Optimization

机译：缓解交通拥堵：通过蜂群优化解决拼车问题

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摘要

Urban road networks in many countries are severely congested. Expanding traffic network capacities by building more roads is very costly as well as environmentally damaging. Researchers, planners, and transportation professionals have developed various Travel Demand Management (TDM) techniques, i.e. strategies that increase travel choices to travelers. Ride sharing is one of the widely used TDM techniques that assumes the participation of two or more persons that together share a vehicle when traveling from few origins to few destinations. In ride-matching systems, commuters wishing to participate in ride sharing are matched by where they live and work, and by their work schedule. There is no standard method in the open literature to determine the best ride-matching method. In this paper, an attempt has been made to develop the methodology capable to solve the ride-matching problem. The proposed Bee Colony Optimization Metaheuristic is sufficiently general and could be applied to various combinatorial optimization problems.
机译：许多国家的城市道路网络严重拥堵。通过修建更多的道路来扩大交通网络的容量不仅成本高昂，而且对环境造成破坏。研究人员，规划人员和运输专业人员已经开发出各种旅行需求管理（TDM）技术，即增加旅行者旅行选择的策略。乘车共享是一种广泛使用的TDM技术，该技术假定两个或两个以上的人从很少的起点到几个目的地旅行时会共同共享一辆车。在乘车匹配系统中，希望参加乘车共享的通勤者通过他们的生活和工作地点以及工作时间表进行匹配。在公开文献中没有标准的方法来确定最佳的乘车匹配方法。在本文中，已经尝试开发能够解决行驶匹配问题的方法。所提出的蜂群优化元启发式方法足够通用，可以应用于各种组合优化问题。

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