Reinforcement learning for the traveling salesman problem with refueling
نویسندگان
چکیده
Abstract 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 paid reinforcement learning (RL) as a potential method solve refueling This paper employs RL With (TSPWR). technique proposes model (actions, states, reinforcements) and RL-TSPWR algorithm. Focus given on analysis parameters influence in cost. Two algorithms: Q-learning SARSA are compared. In addition, parameter estimation performed by Response Surface Methodology, Analysis Variance Tukey Test. proposed achieves best solution 15 out 16 case studies.
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ژورنال
عنوان ژورنال: Complex & Intelligent Systems
سال: 2021
ISSN: ['2198-6053', '2199-4536']
DOI: https://doi.org/10.1007/s40747-021-00444-4