Flexible Job-Shop Scheduling Method for Highly-Distributed Manufacturing Systems

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) with urgent orders constrained by machines, workers. Firstly, a controller designed method for Petri net with uncontrollable transition is introduced, and based on the method, the Petri net model is constructed for urgent jobs in flexible job shop scheduling problem. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Function objectives of the proposed method are to minimize the completion time and the total expense of machines and workers. Finally, Scheduling example is employed to illustrate the effectiveness of the method.

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Modeling and Scheme Generation of Dynamic Flexible Job-Shop Scheduling

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.423-426.2232 ◽

2013 ◽

Vol 423-426 ◽

pp. 2232-2236

Author(s):

Ying Pan ◽

Dong Juan Xue ◽

Tian Yi Gao ◽

Li Bin Zhou ◽

Xiao Yu Xie

Keyword(s):

Dynamic Simulation ◽

Job Shop ◽

Dynamic Scheduling ◽

Job Shop Scheduling ◽

Adaptive Genetic Algorithm ◽

Flexible Job Shop ◽

Uncertain Information ◽

Flexible Job Shop Scheduling ◽

Shop Scheduling ◽

Scheduling Method

Aiming at uncertain information and dynamic characteristic during flexible job-shop scheduling process, some kind of dynamic scheduling method for flexible job-shop scheduling problem (FJSP) is put forward based on real-time adjustment. A dynamic simulation solution mode framework is presented for FJSP. This framework is inspired by adaptive control, combined with the robust scheduling and foreseeing scheduling. It has both advantages of such two scheduling methods, and its stable and highly efficient. Preliminary scheme generation method based on foreseeing dynamics scheduling is introduced then. Foreseeing function is realized by fault-handling algorithm and dynamic simulation solver on the basis of Adaptive Genetic Algorithm (AGA).

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Multi-Objective Flexible Job-Shop Scheduling Method Study Based on The Integration Algorithm of GA-BP

International Journal of Digital Content Technology and its Applications ◽

10.4156/jdcta.vol7.issue2.12 ◽

2013 ◽

Vol 7 (2) ◽

pp. 109-116 ◽

Cited By ~ 1

Author(s):

Defan Zhou ◽

Jingang Jiang ◽

Chunling Luo ◽

Yao Chen

Keyword(s):

Job Shop ◽

Job Shop Scheduling ◽

Flexible Job Shop ◽

Flexible Job Shop Scheduling ◽

Integration Algorithm ◽

Shop Scheduling ◽

Multi Objective ◽

Scheduling Method

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Approach for Multi-Objective Flexible Job Shop Scheduling

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.542-543.407 ◽

2012 ◽

Vol 542-543 ◽

pp. 407-410 ◽

Cited By ~ 3

Author(s):

Hong Jie Hui

Keyword(s):

Petri Net ◽

Job Shop ◽

Job Shop Scheduling ◽

Flexible Job Shop ◽

Flexible Job Shop Scheduling ◽

Job Shop Scheduling Problem ◽

Shop Scheduling ◽

Multi Objective ◽

Scheduling Method ◽

Parikh Vector

A multi-objective scheduling method based on the controlled Petri net and GA is proposed to the flexible job shop scheduling problem (FJSP). Function objectives of the proposed method are to minimize the completion time and the total expense and workload of machines. Firstly, a Parikh vector based approach for Petri net controller is introduced, and based on this method, the Petri net model is constructed for FSP with machine breaking down. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Finally, simulation results based on an example show that the method is efficient.

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