Petri Net and GA Based Method for JSP Optimization with Dual-Objective

2011 ◽  
Vol 121-126 ◽  
pp. 4547-4551
Author(s):  
Li Xin Qi ◽  
Ze Tao
Keyword(s):  
Petri Net ◽  
Supervisory Control ◽  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Linear Constraint ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Scheduling Method

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) constrained by machines, workers. Firstly, a detailed analysis of supervisory control for Petri net with uncontrollable transitions, especially important, for OR-logics linear constraint, a new method for constructing a Petri net feedback controller based on monitor and inhibitor arcs is presented. The Petri net model is constructed based on above method in flexible JSP. 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.

Petri Net with Uncontrollable Transition and GA Based Approach for JSP

2011 ◽  
Vol 48-49 ◽  
pp. 824-829
Author(s):  
Tao Ze ◽  
Xiao Xia Liu
Keyword(s):  
Petri Net ◽  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Scheduling Method

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.

scholarly journals Memetic chicken swarm algorithm for job shop scheduling problem

2019 ◽  
Vol 9 (3) ◽  
pp. 2075 ◽  
Author(s):  
Soukaina cherif bourki Semlali ◽  
Mohammed Essaid Riffi ◽  
Fayçal Chebihi
Keyword(s):  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Swarm Optimization ◽  
Shop Scheduling ◽  
Swarm Algorithm ◽  
Chicken Swarm Optimization

<p>This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.</p>

Approach for Multi-Objective Flexible Job Shop Scheduling

2012 ◽  
Vol 542-543 ◽  
pp. 407-410 ◽  
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.

Job-Shop Scheduling Method Based on Modified Immune Algorithm

2006 ◽  
Vol 315-316 ◽  
pp. 481-485 ◽  
Author(s):  
W.L. Wang ◽  
X.L. Xu ◽  
Yan Wei Zhao ◽  
Q. Guan
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Immune Algorithm ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Adaptive Process ◽  
Automatic Pattern Recognition ◽  
Scheduling Method ◽  
Simulation Results

The mechanism of vaccination was analyzed in the immune system and the improved immune algorithm for the job-shop scheduling problem was presented. The proposed method can reserve the advantage of vaccination and it is independent of the initial antibodies. Especially, the adaptive process of vaccination with the automatic pattern recognition can not only quicken the convergence of the algorithm but also overcome some deficiencies in distilling manually the transcendent knowledge of the problem. Simulation results show that it is an effective approach.

scholarly journals Application of dynamic firework algorithm considering variable neighborhood strategy in flexible job shop scheduling problem

2021 ◽  
Vol 268 ◽  
pp. 01062
Author(s):  
Jie Lv ◽  
Fenqiang Zhang
Keyword(s):  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Processing Cost ◽  
Fitness Value

Aiming at the flexible job shop scheduling problem, this paper constructs a dual-objective mathematical model to minimize the maximum completion time and the minimum total processing cost. The traditional firework algorithm introduces a variable neighborhood search strategy, which is generated during the explosion of the algorithm. On the basis of explosive spark and Gaussian spark, the algorithm is further avoided from falling into the dilemma of local optimization. The product of completion time and processing cost is used as the fitness value of the plan, so that the firework algorithm is suitable for solving the two objective scheduling problems in this paper, and the ratio of fitness value and congestion is used as a comprehensive index for the selection of the optimal plan . In this paper, the selected 5×6 calculation examples are solved, and the completion time of the optimal scheduling scheme is reduced by 12.9%, and the total production cost is reduced by 17.67%, which verifies the feasibility and efficiency of the method.

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