利用遗传算法对马尼拉大都会公共交通系统进行综合优化调度

Cyrill O. Escolano, E. Dadios, Alexis M. Fillone
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引用次数: 2

摘要

交通系统调度方式的选择是调度问题的一个重要方面。本文旨在对高速公路沿线的公共车辆调度进行优化和监控。利用乘客和车辆数据,该系统将分析在覆盖EDSA路线的终端调度puv的最佳调度模式。调度是基于乘客需求和沿线拥堵情况。调度系统将以快速公交系统的调度系统为基础。调度调度有三种模式:正常调度、区域调度和快速调度。它旨在优化调度系统,使乘客在换乘节点的换乘时间最小化,同时满足交通需求、发车时间和最大(最小)车头等操作约束。数学模型说明了系统在不同约束条件下的动力学和行为。采用遗传算法作为优化工具。生成算法所需的数据来自交通调查。代码是用c++程序编写的。结果表明,该系统具有较好的有效性、准确性和鲁棒性。
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An integrated and optimal scheduling of a public transport system in metro Manila using genetic algorithm
Selection of dispatching modes for a transit system is a very important aspect of the schedule problem. This paper aims to optimize and monitor the scheduling and dispatching of public utility vehicles (PUV) plying along EDSA. Using passenger and vehicle data, the system will analyze an optimal scheduling pattern for dispatching PUVs in terminals that covers EDSA routes. The scheduling is based on passenger demand and congestion along the route. The scheduling system will be based on the dispatch system used by the Bus Rapid Transit. There are three modes of dispatch scheduling: normal scheduling, zone scheduling and express scheduling. It seeks to optimize the dispatch system in such a way that the transfer time of passengers at the transfer nodes is minimized while the operational constraints such as the traffic demand, departure time and maximum (minimum) headway are satisfied. Mathematical model illustrates the dynamics and behaviour of the system under different constraints. Genetic algorithm is used as the optimization tool. Data necessary for the generation of the algorithm came from transportation surveys. The code was written using C++ program. Effectiveness, accuracy and robustness of the system are evident by the results.
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