2379. Optimization of Multimodal Tourist Trip Design Using Variable Neighborhood Search
Invited abstract in session WD-59: Urban Mobility II, stream Transportation.
Wednesday, 14:30-16:00Room: Liberty 1.14
Authors (first author is the speaker)
| 1. | HESAMADDIN ELYASI
|
| industrial engineering, ozyegin university | |
| 2. | Milad Elyasi
|
| Industrial Engineering, Ozyegin Universiity | |
| 3. | Okan Ozener
|
| Industrial Engineering, Ozyegin University | |
| 4. | Tom van Woensel
|
| Technische Universiteit Eindhoven |
Abstract
This study addresses the Multimodal Tourist Trip Design Problem (MTTDP), focusing on optimizing personalized travel plans in urban environments, with Istanbul as a case study. The problem involves designing efficient itineraries that integrate various transportation modes, such as walking, public transport, and private vehicles, while considering user preferences, travel time, and cost. We propose an advanced optimization framework using Variable Neighborhood Search (VNS), a metaheuristic algorithm, to explore the solution space effectively. The VNS approach iteratively refines solutions by systematically changing the neighborhoods of current solutions, offering flexibility and the ability to escape local optima. The model incorporates budget constraints and the importance of maximizing user satisfaction across multiple factors. Experimental results show that the VNS-based approach significantly outperforms traditional heuristic methods in terms of efficiency, providing highly personalized, feasible, and cost-effective travel plans for urban tourists.
Keywords
- Transportation
- Metaheuristics
- Vehicle Routing
Status: accepted
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