scholarly journals Grid-Based Hybrid Genetic Approach to Relaxed Flexible Flow Shop with Sequence-Dependent Setup Times

2022 ◽  
Vol 12 (2) ◽  
pp. 607
Author(s):  
Fredy Juárez-Pérez ◽  
Marco Antonio Cruz-Chávez ◽  
Rafael Rivera-López ◽  
Erika Yesenia Ávila-Melgar ◽  
Marta Lilia Eraña-Díaz ◽  
...  

In this paper, a hybrid genetic algorithm implemented in a grid environment to solve hard instances of the flexible flow shop scheduling problem with sequence-dependent setup times is introduced. The genetic algorithm takes advantage of the distributed computing power on the grid to apply a hybrid local search to each individual in the population and reach a near optimal solution in a reduced number of generations. Ant colony systems and simulated annealing are used to apply a combination of iterative and cooperative local searches, respectively. This algorithm is implemented using a master–slave scheme, where the master process distributes the population on the slave process and coordinates the communication on the computational grid elements. The experimental results point out that the proposed scheme obtains the upper bound in a broad set of test instances. Also, an efficiency analysis of the proposed algorithm indicates its competitive use of the computational resources of the grid.

Author(s):  
Toru Eguchi ◽  
Katsutoshi Nishi ◽  
Hiroaki Kawai ◽  
Takeshi Murayama

In this paper, we propose a dynamic job shop scheduling method to minimize tardiness with consideration to sequence dependent setup times. Schedules are optimized on a rolling basis using the mixture of genetic algorithm and switching priority rules. Both in genetic algorithm and switching rules, schedules are generated to increase due date allowances to be robust in dynamic environment. Numerical experiments show the effectiveness of the proposed method.


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