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An ε-Constraint Multi-objective Algorithm for Transit Route Design with Subsidy Consideration

机译:补贴考虑转运路线设计的ε约束多目标算法

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Smart City has been proposed to be a total solution for cities around the world. Public transportation, as one of the basic element in a Smart City, provides shared transport service, such as bus, light rail transit (LRT), and mass rapid transit (MRT), to save energy, reduce air pollution and relieve congestion. For transit operators, how to provide efficient and effective service in traffic networks with limited budget is an important issue. As more public transportation is deployed under the same budget, how to balance bus route and subsidy becomes a new issue. The research proposes a multi-objective formulation to design the optimal bus routes under three conflicting objectives, including travel cost, demand, and subsidy. The solution algorithm is constructed based on the ε-constraint method to solve the problem. Numerical experiments based on a realistic network in Chiayi (Taiwan) are conducted to illustrate the proposed algorithm.
机译:智能城市已被建议为全球城市提供全面解决方案。公共交通,作为智能城市的基本元素之一,提供共用运输服务,如公共汽车,轻轨传输(LRT)和质量快速运输(MRT),以节省能源,减少空气污染和缓解拥堵。对于过境运营商,如何在具有有限预算的交通网络中提供有效和有效的服务是一个重要问题。随着更多公共交通工具在相同的预算下部署,如何平衡巴士路线和补贴成为一个新问题。该研究提出了一种多目标配方,可在三个矛盾的目标下设计最佳总线路线,包括旅行费用,需求和补贴。基于ε-约束方法构建解决方案算法来解决问题。基于Chiayi(台湾)现实网络的数值实验进行了说明了所提出的算法。

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