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Reinforcement and deep reinforcement learning-based solutions for machine maintenance planning, scheduling policies, and optimization
O Ogunfowora, H Najjaran - Journal of Manufacturing Systems, 2023 - Elsevier
Abstract Systems and machines undergo various failure modes that result in machine health
degradation, so maintenance actions are required to restore them back to a state where they …
degradation, so maintenance actions are required to restore them back to a state where they …
Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities
Evolutionary algorithms (EA), a class of stochastic search methods based on the principles
of natural evolution, have received widespread acclaim for their exceptional performance in …
of natural evolution, have received widespread acclaim for their exceptional performance in …
A cooperative scatter search with reinforcement learning mechanism for the distributed permutation flowshop scheduling problem with sequence-dependent setup …
F Zhao, G Zhou, L Wang - IEEE Transactions on Systems, Man …, 2023 - ieeexplore.ieee.org
The integration of reinforcement learning technology into meta-heuristic algorithms to
address complex combinatorial optimization problems has attracted much attention in recent …
address complex combinatorial optimization problems has attracted much attention in recent …
A novel shuffled frog-lea** algorithm with reinforcement learning for distributed assembly hybrid flow shop scheduling
Distributed hybrid flow shop scheduling (DHFS) problem has attracted much attention in
recent years; however, DHFS with actual processing constraints like assembly is seldom …
recent years; however, DHFS with actual processing constraints like assembly is seldom …
Q-learning driven multi-population memetic algorithm for distributed three-stage assembly hybrid flow shop scheduling with flexible preventive maintenance
Y Jia, Q Yan, H Wang - Expert Systems with Applications, 2023 - Elsevier
The distributed assembly flow shop scheduling (DAFS) problem has received much
attention in the last decade, and a variety of metaheuristic algorithms have been developed …
attention in the last decade, and a variety of metaheuristic algorithms have been developed …
Ensemble meta-heuristics and Q-learning for solving unmanned surface vessels scheduling problems
M Gao, K Gao, Z Ma, W Tang - Swarm and Evolutionary Computation, 2023 - Elsevier
This work addresses multiple unmanned surface vessel (USV) scheduling problems with
minimizing maximum completion time. First, a mathematical model is developed with …
minimizing maximum completion time. First, a mathematical model is developed with …
Scheduling eight-phase urban traffic light problems via ensemble meta-heuristics and Q-learning based local search
This paper addresses urban traffic light scheduling problems (UTLSP) with eight phases.
The objective is to minimize the total vehicle delay time by assigning traffic phases and …
The objective is to minimize the total vehicle delay time by assigning traffic phases and …
A Q-learning based multi-strategy integrated artificial bee colony algorithm with application in unmanned vehicle path planning
X Ni, W Hu, Q Fan, Y Cui, C Qi - Expert Systems with Applications, 2024 - Elsevier
Artificial bee colony (ABC) is a prominent algorithm that offers great exploration capabilities
among various meta-heuristic algorithms. However, its monotonous and one-dimensional …
among various meta-heuristic algorithms. However, its monotonous and one-dimensional …
Q-learning based multi-objective immune algorithm for fuzzy flexible job shop scheduling problem considering dynamic disruptions
X Chen, J Li, Y Xu - Swarm and Evolutionary Computation, 2023 - Elsevier
Confronted with complex industrial environments, dynamic disruptions like new job arrival
and machine breakdown bring significant challenges to the robustness and stability of the …
and machine breakdown bring significant challenges to the robustness and stability of the …
Learning-based production, maintenance, and quality optimization in smart manufacturing systems: A literature review and trends
With the introduction of manufacturing paradigms, including Industry 4.0, production
research has shifted its focus to enabling intelligent manufacturing systems within industrial …
research has shifted its focus to enabling intelligent manufacturing systems within industrial …