A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios

Guardado en:

Detalles Bibliográficos
Publicado en:	ISPRS International Journal of Geo-Information vol. 14, no. 12 (2025), p. 461-484
Autor principal:	Lyu Yijie
Otros Autores:	Tang Zhongan, Li, Yalun, Liu Baoju, Deng, Min, Wu, Guohua
Publicado:	MDPI AG
Materias:	Integer programming Misalignment Urban environments Collaboration Adaptability Optimization Order quantity Decision making Heuristic Urban areas Reinforcement Heterogeneity Heuristic methods Efficiency Patchiness Policies Mathematical programming Neural networks Spatial heterogeneity Learning Linear programming Methods Multiagent systems Electronic commerce Algorithms Logistics Deep learning
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Sea el primero en dejar un comentario!