Abstract
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.
| Original language | English |
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| Title of host publication | 2022 IEEE International Conference on Smart Mobility, SM 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 32-37 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665499545 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 2022 IEEE International Conference on Smart Mobility, SM 2022 - Virtual, Online, Egypt Duration: 6 Mar 2022 → 7 Mar 2022 |
Publication series
| Name | 2022 IEEE International Conference on Smart Mobility, SM 2022 |
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Conference
| Conference | 2022 IEEE International Conference on Smart Mobility, SM 2022 |
|---|---|
| Country/Territory | Egypt |
| City | Virtual, Online |
| Period | 6/03/22 → 7/03/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- Trip planning
- bio-inspired algorithms
- genetic algorithms and artificial bee colony algorithm
- meta-heuristics
- multi-criteria optimization
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Control and Optimization