A hybrid genetic tabu search algorithm for distributed flexible job shop scheduling problems
Author:
Funder
National Natural Science Foundation of China
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,Hardware and Architecture,Software,Control and Systems Engineering
Reference36 articles.
1. Look-ahead based reinforcement learning for robotic flow shop scheduling;Kim;J Manuf Syst,2023
2. A hyperheuristic with Q-learning for the multiobjective energy-efficient distributed blocking flow shop scheduling problem;Zhao;IEEE Trans Cyber,2023
3. Discrete evolutionary multi-objective optimization for energy-efficient blocking flow shop scheduling with setup time;Han;Appl Soft Comput,2020
4. A multi-agent system simulation based approach for collision avoidance in integrated job-shop scheduling problem with transportation tasks;Sanogo;J Manuf Syst,2023
5. Necessary and sufficient conditions for feasible neighbourhood solutions in the local search of the job-shop scheduling problem;Gui;Chin J Mech Eng,2023
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1. Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources;Robotics and Computer-Integrated Manufacturing;2024-10
2. A learning-driven multi-objective cooperative artificial bee colony algorithm for distributed flexible job shop scheduling problems with preventive maintenance and transportation operations;Computers & Industrial Engineering;2024-10
3. Dynamic scheduling of hybrid flow shop problem with uncertain process time and flexible maintenance using NeuroEvolution of Augmenting Topologies;IET Collaborative Intelligent Manufacturing;2024-09
4. Solving Flexible Job-Shop Scheduling Problem with Heterogeneous Graph Neural Network Based on Relation and Deep Reinforcement Learning;Machines;2024-08-22
5. An Integrated Process Planning and Scheduling problem solved from an adaptive multi-objective perspective;Journal of Manufacturing Systems;2024-08
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