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Modified A* Algorithm integrated with ant colony optimization for multi-objective route-finding; case study: Yazd
Applied Soft Computing ( IF 8.7 ) Pub Date : 2021-09-17 , DOI: 10.1016/j.asoc.2021.107877
Leila Pasandi 1 , Mehrnaz Hooshmand 1 , Morteza Rahbar 2
Affiliation  

In this paper, MASA (Modified A* Algorithm) method is introduced which can merge numerous factors with different weights into a multi-weighted graph to offer the most optimal route for a pedestrian tourist. Several mobile applications support personalized tour recommendations in making feasible plans, however, tours should not only make visiting attractions possible via the shorter route but also satisfy the unique needs of individuals with different preferences. MASA integrates the Ant Colony Optimization algorithm for arranging points of interest (POI), with a modified A* algorithm for generating multi-weighted graphs through pairs of POIs to propose the most suitable tour and facilitate traversal for a tourist who does not get involved with riding vehicles. Our contribution in this research is to consider multiple factors simultaneously or customize the route based on the user’s choice, and introduce pareto front chart for selecting optimal links, which has not been solved yet for being a challenging as well as complicated case. The user in this paper is authorized to choose preferred POIs, defined the importance of each parameter to affect route finding. A historical region in Yazd is selected as the case study due to its winding streets to show the solidity of our approach, with four main factors including Length, Communion, Relaxation, and Isovist, and then three routes have been generated considering customized selections along with an overall route considering all objectives. The computational results have shown the capability of the new proposed algorithm in route finding.



中文翻译:

改进的A*算法结合蚁群优化进行多目标寻路;案例研究:亚兹德

本文引入了MASA(Modified A* Algorithm)方法,该方法可以将众多不同权重的因素合并成一个多权重图,为步行游客提供最佳路线。一些移动应用程序支持个性化的旅游推荐以制定可行的计划,但旅游不仅要使游览景点的路线更短,还要满足不同喜好的个人的独特需求。MASA 集成了用于安排兴趣点 (POI) 的蚁群优化算法,以及改进的 A* 算法,用于通过成对的 POI 生成多权重图,以提出最合适的旅游路线,并为不涉足的游客提供便利乘坐车辆。我们在这项研究中的贡献是同时考虑多个因素或根据用户的选择定制路线,并引入帕累托前沿图来选择最佳链接,该问题由于具有挑战性和复杂性而尚未解决。本文中的用户有权选择首选 POI,定义每个参数对路径查找的重要性。选择亚兹德的一个历史地区作为案例研究,因为它的街道蜿蜒曲折,以展示我们方法的稳健性,包括长度、圣餐、放松和 Isovist 四个主要因素,然后考虑定制选择生成了三条路线以及考虑所有目标的总体路线。计算结果表明了新算法在寻路方面的能力。

更新日期:2021-09-29
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