Generative inverse reinforcement learning for learning 2-opt heuristics without extrinsic rewards in routing problems

Generative inverse reinforcement learning for learning 2-opt heuristics without extrinsic rewards in routing problems

Deep reinforcement learning (DRL) has shown promise in solving challenging combinatorial optimization (CO) problems, such as the traveling salesman problem (TSP) and vehicle routing problem (VRP). However, existing DRL methods rely on manually designed reward functions, which may be inaccurate or un...

Bibliográfalaš dieđut
Váldodahkkit:	Qi Wang, Yongsheng Hao, Jiawei Zhang
Materiálatiipa:	Artihkal
Giella:	English
Almmustuhtton:	Elsevier 2023-10-01
Ráidu:	Journal of King Saud University: Computer and Information Sciences
Fáttát:	Routing problems Deep reinforcement learning Generative adversarial networks 2-opt heuristics Inverse reinforcement learning
Liŋkkat:	http://www.sciencedirect.com/science/article/pii/S1319157823003415

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