Trip Itinerary Planning: A Bio-inspired Metaheuristic Approach

被引：0
|
作者：
Jia, Jingkai [1 ]
Chen, Yuli [1 ]
Liu, Yuxuan [1 ]
Khamis, Alaa [2 ]
机构：
[1] Univ Toronto, Elect & Comp Engn, Toronto, ON, Canada
[2] Gen Motors Canada, Canadian Tech Ctr, Oshawa, ON, Canada
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON SMART MOBILITY (ICSM 2022) | 2022年
关键词：
Trip planning; multi-criteria optimization; meta-heuristics; bio-inspired algorithms; genetic algorithms and artificial bee colony algorithm; TEAM ORIENTEERING PROBLEM; ALGORITHM;
D O I：
10.1109/SM55505.2022.9758204
中图分类号：
学科分类号：
摘要：
Trip itinerary planning plays an important role in the tourism industry and in our daily lives. In this paper, trip itinerary planning problem is modelled as Team Orienteering Problem with Time Window (TOPTW) with travel distance as a soft constraint. Three bio-inspired meta-heuristic algorithms, namely, genetic algorithm, adaptive genetic algorithm and artificial bee colony algorithm are considered to solve this problem. These solvers are evaluated in terms of algorithms' execution time, optimality, and coverage time using real data from City of Toronto. The experiment results show that adaptive genetic algorithm outperforms the other algorithms in terms of optimality and robustness.
引用
收藏
页码：32 / 37
页数：6
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