應用粒子群演算法於考量乘客上下車屬性之公車路網排班問題研究

Applications of Particle Swarm Optimization for Bus Route Network Scheduling Problem with Passenger Properties

王宣晴(Syuan-Cing Wang)

指導教授 ： 楊康宏

中原大學/電機資訊學院/工業與系統工程研究所/碩士(2018年)

https://doi.org/10.6840/cycu201800691

摘要

隨著與人口成長與經濟的快速發展，私有汽車的增加使交通因此變得擁擠而缺乏效率，同時也造成了空氣的污染。良好的公共交通運輸服務，能使民眾的搭乘意願提高，將有助改善都市的交通壅塞及環境污染的問題。公共交通運輸工具當中，公車為民眾使用次數最多的一項，為了提升民眾搭乘公共交通運輸工具之意願，公共交通服務品質的改善及良好的公共交通運輸規劃成為重要的課題。故本研究為提升公車的服務品質，以粒子群演算法編寫一考量乘客屬性的公車路網排班演算法，將公車路網排班問題分為三個子問題並以多層的粒子群演算法進行求解，目標為最小化未上車之人數。根據等待人數的平均值與變異係數分為4個情境進行分析，其結果顯示本研究所建立之演算法，在不同情境下可以穩定求解。

關鍵字

公車排班問題 ； 路網排班問題 ； 乘客屬性 ； 粒子群演算法

並列摘要

With the rapid development of population growth and economy, the increase in private cars has made traffic crowded and inefficient, and it has also caused air pollution.
Public transportation services increases the willingness of people to travel and helps improve traffic congestion and environmental pollution in urban areas. Among the public transportation vehicles, buses are the most frequently used by the public. In order to improve people's willingness to take public transportation, the improvement of public transportation service quality and good public transportation planning have become important issues.
In order to improve the service quality of the bus, this study establishes a bus network scheduling algorithm based on the particle swarm algorithm to consider the passenger property. The bus network scheduling problem is divided into three sub-problems and solved by multi-layer particle swarm algorithm. The goal is to minimize the number of people who have not boarded the bus.
According to the average of waiting people and the coefficient of variation, it is divided into four scenarios for analysis. The results show that the algorithm established in this study can be solved stably under different situations.

並列關鍵字

Bus route network scheduling problem ； Passenger properties ； Particle swarm optimization

參考文獻

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