Deep Reinforcement Learning Algorithms for Heterogeneous Multiple Knapsack Problems

By focusing on the traditional multi-Knapsack Problem (KP) in typical logistics system operations, this study abstracts a Heterogeneous Multiple Knapsack Problem (HMKP) and formulates an improved Deep Deterministic Policy Gradient (DDPG) algorithm to solve it. The DDPG algorithm tends to fall into a...

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Autor principal:	LI Bin, GUO Yi
Format:	Artigo
Idioma:	Inglês
Publicat:	Editorial Office of Computer Engineering 2026-04-01
Col·lecció:	Jisuanji gongcheng
Matèries:	deep reinforcement learning (drl)|0-1 knapsack problem (kp)|heterogeneous multiple knapsack problem (hmkp)|transformer module|dynamic penalty mechanism|tabu list
Accés en línia:	https://www.ecice06.com/fileup/1000-3428/PDF/20260411.pdf
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