Eskisehir城市移动出行计划器三种搜索算法的比较

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2015-09-28 DOI:10.1109/INISTA.2015.7276791

A. Aydin, Sedat Telçeken

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引用次数: 2

摘要

三种搜索算法的比较;针对土耳其埃斯基谢希尔市的移动出行规划应用，提出了一种基于蚁群优化和遗传算法的旅行者推销员问题求解方法。该算法适用于30多个兴趣点和150个子兴趣点。在具有不同兴趣点数量的场景下，比较了算法的运行时间。实验结果表明，A*算法的速度比其他算法快400-600%。这款手机应用程序会根据旅行者对不同兴趣点的偏好，计算出最佳旅行路线。这款手机应用程序还会在旅行者提前或晚于行程计划的情况下，推荐其他路线计划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparison of three search algorithms for mobile trip planner for Eskisehir city

The comparison of three searching algorithms; A*, Ant Colony Optimization and Genetic Algorithms to solve the Traveler Salesman Problem for a mobile trip planning application for Eskisehir City, Turkey, is presented in this paper. The algorithms work on more than 30 point-of-interests and 150 sub-point-of-interests. The algorithms are compared with respect to their running times for scenarios with different number of point-of-interests. Experimental results show that the A* algorithm is 400-600% faster than the other algorithms. The mobile application calculates the best route trip planned according to the traveler's preferences on categorized points-of-interests. The mobile application also recommends alternative route plans during the trip when the traveler is ahead or behind the schedule.

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来源期刊

2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)

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