Dynamic Vehicle Routing under Uncertain Travel Costs and Refueling Opportunities

Polychronis, Giorgos; Lalis, Spyros

doi:10.5220/0007673900520063

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2021

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“…Vehicle refueling problems have been extensively investigated [25,27,36,42,43,56,57,62,[69][70][71]. One of the lines of study is the fixed route vehicle refueling problem (FRVRP), where the goal is to select the refueling points on a fixed route.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement learning for the traveling salesman problem with refueling

Ottoni

Nepomuceno

Oliveira

et al. 2021

Complex Intell. Syst.

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The traveling salesman problem (TSP) is one of the best-known combinatorial optimization problems. Many methods derived from TSP have been applied to study autonomous vehicle route planning with fuel constraints. Nevertheless, less attention has been paid to reinforcement learning (RL) as a potential method to solve refueling problems. This paper employs RL to solve the traveling salesman problem With refueling (TSPWR). The technique proposes a model (actions, states, reinforcements) and RL-TSPWR algorithm. Focus is given on the analysis of RL parameters and on the refueling influence in route learning optimization of fuel cost. Two RL algorithms: Q-learning and SARSA are compared. In addition, RL parameter estimation is performed by Response Surface Methodology, Analysis of Variance and Tukey Test. The proposed method achieves the best solution in 15 out of 16 case studies.

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