Results 241 to 250 of about 22,784 (309)

A Learning-Based Multipopulation Evolutionary Optimization for Flexible Job Shop Scheduling Problem With Finite Transportation Resources

IEEE Transactions on Evolutionary Computation, 2023
In many practical manufacturing systems, transportation equipment such as automated guided vehicles (AGVs) is widely adopted to transfer jobs and realize the collaboration of different machines, but is often ignored in current researches. In this article,
Zixiao Pan, Ling Wang, Jie Zheng, Jing-fang Chen, Xing Wang   +4 more
semanticscholar   +1 more source

A Two-Stage Individual Feedback NSGA-III for Dynamic Many-Objective Flexible Job Shop Scheduling Problem

IEEE Transactions on Automation Science and Engineering
Dynamic events, such as machine fault and rush order insertion, are fairly common in the job shop scheduling, which may lead to significant delay in order delivery and low production efficiency.
Yi Feng, Yating Lin, Zhile Yang, Yunlang Xu, Di Li, Xiaoou Li, Dongsheng Yang   +6 more
semanticscholar   +1 more source

Co-Evolution With Deep Reinforcement Learning for Energy-Aware Distributed Heterogeneous Flexible Job Shop Scheduling

IEEE Transactions on Systems, Man, and Cybernetics: Systems
Energy-aware distributed heterogeneous flexible job shop scheduling (DHFJS) problem is an extension of the traditional FJS, which is harder to solve. This work aims to minimize total energy consumption (TEC) and makespan for DHFJS.
Rui Li, Wenyin Gong, Ling Wang, Chao Lu, Chenxin Dong   +4 more
semanticscholar   +1 more source

A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem

Computers & industrial engineering, 2020
As an important branch of production scheduling, flexible job-shop scheduling problem (FJSP) is difficult to solve and is proven to be NP-hard. Many intelligent algorithms have been proposed to solve FJSP, but their key parameters cannot be dynamically ...
Ronghua Chen, Bo Yang, Shi Li, Shilong Wang   +3 more
semanticscholar   +1 more source

Real-Time Scheduling for Flexible Job Shop With AGVs Using Multiagent Reinforcement Learning and Efficient Action Decoding

IEEE Transactions on Systems, Man, and Cybernetics: Systems
The application of automated guided vehicle (AGV) greatly improves the production efficiency of workshop. However, machine flexibility and limited logistics equipment increase the complexity of collaborative scheduling, and frequent dynamic events bring ...
Yuxin Li, Qingzheng Wang, Xinyu Li, Liang Gao, Ling Fu, Yanbin Yu, Wei Zhou   +6 more
semanticscholar   +1 more source

Evaluating Schedule Performance in Flexible Job-Shops

2004
In this paper, we are interested in the multi-objective evaluation of the schedule performance in the flexible job shops. The Flexible Job Shop Scheduling Problem (FJSP) is known in the literature as one of the hardest combinatorial optimization problems and presents many objectives to be optimized.
Kacem, Imed, Borne, Pierre
openaire   +2 more sources

Genetic Programming With Lexicase Selection for Large-Scale Dynamic Flexible Job Shop Scheduling

IEEE Transactions on Evolutionary Computation
Dynamic flexible job shop scheduling (JSS) is a prominent combinatorial optimization problem with many real-world applications. Genetic programming (GP) has been widely used to automatically evolve effective scheduling heuristics for dynamic flexible JSS
Meng Xu, Yi Mei, Fangfang Zhang, Mengjie Zhang   +3 more
semanticscholar   +1 more source

Scheduling flexible job shops under workforce constraints

2021
Scheduling problems are of high relevance in various application areas, especially in production and logistic environments. A well-known problem setting is the job shop scheduling problem that occurs in traditional manufacturing systems. Modern manufacturing systems, however, are usually more complex and feature multi-purpose machines that allow to ...
openaire   +1 more source

Flexible job shop scheduling via deep reinforcement learning with meta-path-based heterogeneous graph neural network

Knowledge-Based Systems
The flexible job shop scheduling problem (FJSP) is an important production scheduling problem in intelligent manufacturing. How to model the complex FJSP more accurately and improve the efficiency and generalization of scheduling policies is an urgent ...
Lanjun Wan, Long Fu, Changyun Li, Keqin Li   +3 more
semanticscholar   +1 more source

Task Relatedness-Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling

IEEE Transactions on Evolutionary Computation, 2023
Multitask learning has been successfully used in handling multiple related tasks simultaneously. In reality, there are often many tasks to be solved together, and the relatedness between them is unknown in advance.
Fangfang Zhang, Yi Mei, Su Nguyen, K. Tan, Mengjie Zhang   +4 more
semanticscholar   +1 more source