Results 191 to 200 of about 87,297 (252)

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

A review of flexible job shop scheduling problems considering transportation vehicles

Frontiers of Information Technology & Electronic Engineering
The flexible job shop scheduling problem for processing machines and transportation vehicles (FJSP_PT) has garnered significant attention from academia and industry.
Bin Xin, Sai Lu, Qing Wang, Fang Deng
semanticscholar   +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

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

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

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

Optimal scheduling for flexible job shop operation

International Journal of Production Research, 2005
This paper presents a new integer linear programming (ILP) model to schedule flexible job shop, discrete parts manufacturing industries that operate on a make-to-order basis. The model considers groups of parallel homogeneous machines, limited intermediate buffers and negligible set-up effects.
M.C. Gomes *, A.P. Barbosa-Póvoa, A.Q. Novais   +2 more
openaire   +1 more source

Flexible Job-Shop Scheduling Problems

2005
Planning and scheduling problems in various industrial environments are combinatorial and very difficult. Generally, it is extremely hard to solve these types of problems in their general form. Scheduling can be formulated as a problem of determining the best sequence to execute a set of tasks on a set of resources, respecting specific constraints like
openaire   +2 more sources

A reinforcement learning enhanced memetic algorithm for multi-objective flexible job shop scheduling toward Industry 5.0

International Journal of Production Research
Flexible job shop scheduling problem (FJSP) with worker flexibility has gained significant attention in the upcoming Industry 5.0 era because of its computational complexity and its importance in production processes.
Xiao Chang, Xiaoliang Jia, Jiahao Ren
semanticscholar   +1 more source

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