Solving large scale industrial production scheduling problems with complex constraints: an overview of the state-of-the-art
M Schlenkrich, SN Parragh - Procedia Computer Science, 2023 - Elsevier
Production scheduling is challenging and the body of literature addressing various variants
of the problem is large. It can roughly be divided into two streams: The first stream addresses …
of the problem is large. It can roughly be divided into two streams: The first stream addresses …
A cooperative hierarchical deep reinforcement learning based multi-agent method for distributed job shop scheduling problem with random job arrivals
Distributed manufacturing can reduce the production cost through the cooperation among
factories, and it has been an important trend in the industrial field. For the enterprises with …
factories, and it has been an important trend in the industrial field. For the enterprises with …
Deep reinforcement learning for dynamic distributed job shop scheduling problem with transfers
Y Lei, Q Deng, M Liao, S Gao - Expert Systems with Applications, 2024 - Elsevier
Dynamic events and transportation constraints would significantly affect the full utilization of
resources and the reduction of production costs in distributed job shops. Therefore, in this …
resources and the reduction of production costs in distributed job shops. Therefore, in this …
[HTML][HTML] Machine Learning to Estimate Workload and Balance Resources with Live Migration and VM Placement
Currently, utilizing virtualization technology in data centers often imposes an increasing
burden on the host machine (HM), leading to a decline in VM performance. To address this …
burden on the host machine (HM), leading to a decline in VM performance. To address this …
Sustainable scheduling of TFT-LCD cell production: A hybrid dispatching rule and two-phase genetic algorithm
HK Wang, CW Chou, CH Wang, LA Ho - International Journal of Production …, 2024 - Elsevier
TFT-LCD manufacturing process involves Array, Color Filter (CF), Cell, and Module. The
Cell process is pivotal in the TFT-LCD production supply chain; it bridges the front-end …
Cell process is pivotal in the TFT-LCD production supply chain; it bridges the front-end …
A Hierarchical Multi-Action Deep Reinforcement Learning Method for Dynamic Distributed Job-Shop Scheduling Problem With Job Arrivals
The Distributed Job-shop Scheduling Problem (DJSP) is a significant issue in both
academic and industrial fields. In real-world production, uncertain disturbances such as job …
academic and industrial fields. In real-world production, uncertain disturbances such as job …
Learning to schedule (L2S): Adaptive job shop scheduling using double deep Q network
AD Workneh, M Gmira - Smart Science, 2023 - Taylor & Francis
The stochasticity and randomly changing nature of the production environment posed a
significant challenge in develo** real-time responsive scheduling solutions. Many …
significant challenge in develo** real-time responsive scheduling solutions. Many …
AI-Driven Optimization Approach Based on Genetic Algorithm in Mass Customization Supplying and Manufacturing.
S Alfayoumi, N Eltazi… - International Journal of …, 2023 - search.ebscohost.com
Numerous artificial intelligence (AI) techniques are currently utilized to identify planning
solutions for supply chains, which comprise suppliers, manufacturers, wholesalers, and …
solutions for supply chains, which comprise suppliers, manufacturers, wholesalers, and …
Effect of backtracking strategy in population-based approach: the case of the set-union knapsack problem
In this article, we study the effect of the backtracking strategy when injected into solutions
related to a population-based approach, especially when tackling the set-union knapsack …
related to a population-based approach, especially when tackling the set-union knapsack …
Dynamic Job Shop Scheduling Problem with New Job Arrivals using Hybrid Genetic Algorithm
The paper tackles the dynamic job shop scheduling problem (DJSSP), aiming to schedule a
new set of jobs while minimizing the completion time of all operations. This paper proposes …
new set of jobs while minimizing the completion time of all operations. This paper proposes …