2614. Exploring right-hand side uncertainty for insular vehicle routing problems
Invited abstract in session MB-27: Vehicle Routing under Uncertainty , stream Stochastic and Robust optimization.
Monday, 10:30-12:00Room: Maurice Keyworth G.02
Authors (first author is the speaker)
| 1. | Javier Maturana-Ross
|
| School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso | |
| 2. | Stefan Voss
|
| Wirtschaftsinformatik/Information Systems, University of Hamburg | |
| 3. | Benjamin Peso
|
| Pontificia Universidad Católica de Valparaíso |
Abstract
The Bi-Objective Insular Traveling Salesman Problem (BO-InTSP) is used to optimize freight logistics in island networks by minimizing maritime (MTC) and ground transportation costs (GTC). While exact formulations from literature are available, related deterministic assumptions ignore real-world uncertainties like fluctuating port capacities (weather, labor shortages). This study integrates right-hand-side (RHS) uncertainty into the BO-InTSP and attempts to solve it with inspiration from existing solution approaches from production scheduling and robust vehicle routing. That is, we propose a matheuristic framework combining exact methods (AUGMECON2) with metaheuristics (Variable Neighborhood Search, Fixed Set Search) to handle this complex problem. Stochastic port capacities are modeled via scenarios (e.g., 80%, 100%, 120% of a baseline), ensuring that solutions remain feasible under disruptions. Scenario generation aligns with robust optimization principles, retaining solutions that meet at least 90% of the feasibility thresholds. This hybrid approach balances rigorous Pareto-front generation with adaptive exploration, addressing a critical gap in island logistics research.
Keywords
- Transportation
- Robust Optimization
- Stochastic Optimization
Status: accepted
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