Two-stage teaching-learning-based optimization method for flexible job-shop scheduling under machine breakdown

2018 ◽  
Vol 100 (5-8) ◽  
pp. 1419-1432 ◽  
Author(s):  
Raviteja Buddala ◽  
Siba Sankar Mahapatra
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Method ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Two Stage ◽  
Machine Breakdown ◽  
Shop Scheduling ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

NSGA-II applied to dynamic flexible job shop scheduling problems with machine breakdown

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840111 ◽  
Author(s):  
Chao Chen ◽  
Zhicheng Ji ◽  
Yan Wang
Keyword(s):  
Job Shop ◽  
Dynamic Scheduling ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Nsga Ii ◽  
Machine Breakdown ◽  
Shop Scheduling ◽  
Multi Objective ◽  
The Impact

This paper focuses on multi-objective dynamic flexible job shop scheduling problem (MODFJSP) with machine breakdown. First, a multi-objective dynamic scheduling model is established, with objectives to minimize makespan and total machine workload. Second, according to the processing status of faulty machine, a hybrid rescheduling strategy including transfer rescheduling strategy and complete rescheduling strategy is proposed to react to stochastic machine breakdown. The performance of two rescheduling strategies is analyzed in terms of the scheduling efficiency and its stability, from the delay extent and initial scheduling deviation, respectively. Besides, the optimal adaptation conditions of both scheduling strategies are obtained. Furthermore, the non-dominated sorting genetic algorithm (NSGA-II) is employed to solve the constructed model. Experimental results demonstrate the effectiveness of the proposed strategies on reducing the impact of machine breakdown in real scheduling.

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