Scheduling of twin automated stacking cranes based on Deep Reinforcement Learning
X Jin, N Mi, W Song, Q Li - Computers & Industrial Engineering, 2024 - Elsevier
Effective scheduling of twin automated stacking cranes (ASCs) in automated storage yard is
critical to maximize operational efficiency. While Deep Reinforcement Learning (DRL) is …
critical to maximize operational efficiency. While Deep Reinforcement Learning (DRL) is …
Analysis of box and ellipsoidal robust optimization, and attention model based reinforcement learning for a robust vehicle routing problem
S Hansuwa, MR Velayudhan Kumar… - Sādhanā, 2022 - Springer
In this work, we consider a class of vehicle routing problem that uses simultaneous pickup
and delivery and is constrained by a hard service time window with an objective to minimize …
and delivery and is constrained by a hard service time window with an objective to minimize …
An AI-based Simulation and Optimization Framework for Logistic Systems
Improving logistics efficiency is a challenging task in logistic systems, since planning the
vehicle routes highly relies on the changing traffic conditions and diverse demand …
vehicle routes highly relies on the changing traffic conditions and diverse demand …
A Network Fault Prediction‐Based Service Migration Approach for Unstable Mobile Edge Environment
H Wang, W Tang, J Luo - Wireless Communications and …, 2023 - Wiley Online Library
How to perform efficient service migration in a mobile edge environment has become one of
the research hotspots in the field of service computing. Most service migration approaches …
the research hotspots in the field of service computing. Most service migration approaches …
Reinforcement Learning based Hyper-heuristics for Many-objective Pickup and Delivery Problem
AA Anwar, X Zhang - 2023 IEEE International Conference on …, 2023 - ieeexplore.ieee.org
The pickup and delivery problem (PDP) is considered one of the key optimization problems.
PDP is an NP-Hard problem; consequently, researchers tried to solve it using evolutionary …
PDP is an NP-Hard problem; consequently, researchers tried to solve it using evolutionary …
基于交通预测信息的电动汽车充电路径规划
师泽宇， 陈阳舟， 安树科 - 北京工业大学学报, 2024 - journal.bjut.edu.cn
针对电动汽车充电路径规划问题, 以行程时间为优化目标, 以荷电状态作为硬性约束,
基于预测交通状态标定的动态异构交通网及车辆动力学模型, 构建最优控制问题. 为了在线求解 …
基于预测交通状态标定的动态异构交通网及车辆动力学模型, 构建最优控制问题. 为了在线求解 …
Reinforcement learning for the pickup and delivery problem
F Liu, C Lai, L Wang - International Conference on Artificial Neural …, 2022 - Springer
The pickup and delivery problem (PDP) and its related variants are an important part in the
field of urban logistics and distribution, and there are many heuristic algorithms to solve …
field of urban logistics and distribution, and there are many heuristic algorithms to solve …
Enhancing Courier Scheduling in Crowdsourced Last-Mile Delivery through Dynamic Shift Extensions: A Deep Reinforcement Learning Approach
Crowdsourced delivery platforms face complex scheduling challenges to match couriers and
customer orders. We consider two types of crowdsourced couriers, namely, committed and …
customer orders. We consider two types of crowdsourced couriers, namely, committed and …
基于局部位置感知的多智能体网约车调度方法.
黄晓辉， 凌嘉壕， 张雄， 熊李艳… - Journal of Computer …, 2023 - search.ebscohost.com
近年来, 网上约车成为人们日常出行不可或缺的一部分. 网约车平台的核心任务是如何有效地把
订单派送给合适的司机, 使得用户总体等待时间尽可能短, 而司机的收益尽可能高 …
订单派送给合适的司机, 使得用户总体等待时间尽可能短, 而司机的收益尽可能高 …
Deep reinforcement learning for the capacitated vehicle routing problem with soft time window
W Xiaohe, S Xinli - 2022 14th International Conference on …, 2022 - ieeexplore.ieee.org
The past decade has seen a rapid development of solving travelling salesman problem
(TSP) and vehicle routing problem (VRP) with deep reinforcement learning. In order to solve …
(TSP) and vehicle routing problem (VRP) with deep reinforcement learning. In order to solve …