An elitist nondominated sorting hybrid algorithm for multi-objective flexible job-shop scheduling problem with sequence-dependent setups

2019 ◽  
Vol 173 ◽  
pp. 83-112 ◽  
Author(s):  
Z.C. Li ◽  
B. Qian ◽  
R. Hu ◽  
L.L. Chang ◽  
J.B. Yang
Keyword(s):  
Hybrid Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Nondominated Sorting

A Novel Variable Neighborhood Genetic Algorithm for Multi-Objective Flexible Job-Shop Scheduling Problems

2010 ◽  
Vol 118-120 ◽  
pp. 369-373 ◽  
Author(s):  
Guo Hui Zhang ◽  
Liang Gao ◽  
Yang Shi
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective

Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. It is quite difficult to achieve optimal or near-optimal solutions with single traditional optimization approach because the multi objective FJSP has the high computational complexity. An novel hybrid algorithm combined variable neighborhood search algorithm with genetic algorithm is proposed to solve the multi objective FJSP in this paper. An external memory is adopted to save and update the non-dominated solutions during the optimization process. To evaluate the performance of the proposed hybrid algorithm, benchmark problems are solved. Computational results show that the proposed algorithm is efficient and effective approach for the multi objective FJSP.

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