基于遗传算法的收费站队列选择器实现

K. Obias, E. Magsino
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引用次数: 0

摘要

本文对一种基于遗传算法的高速公路收费站智能选择器进行了广泛的探索和仿真,使车辆能够尽可能快速方便地进出收费站。道路用户的便利性是根据等待时间和队列长度来衡量的,而基础设施的效率是根据服务器利用率来评估的。将探索性遗传策略(GAQ)与最短队列策略(SQ)和模糊逻辑策略(FLCQ)进行了比较。与SQ相比,GAQ提供了更好的性能,但在快速服务时间内,FLCQ的性能优于GAQ。根据这些观察结果,我们提出了改进GAQ性能的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing a Tollgate Queue Selector Based on Genetic Algorithm
In this work, an intelligent highway tollgate selector based on genetic algorithm is explored and simulated extensively to allow vehicles to enter or exit the tollbooth as quickly and conveniently as possible. Road user convenience is measured in terms of waiting time and queue length, while infrastructure efficiency is evaluated in terms of the server utilization. Our exploratory genetic-based policy (GAQ) is compared to the shortest queue (SQ) and fuzzy logic-based (FLCQ) policies. GAQ provides an improved performance when compared to SQ, but is outperformed by FLCQ during fast service times. Given these observations, we then provided suggestions to improve the GAQ performance.
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