A genetic algorithm for solving a hybrid flexible flowshop with sequence dependent setup times

2013 ◽  
Author(s):  
Aymen Sioud ◽  
Marc Gravel ◽  
Caroline Gagne
Keyword(s):  
Genetic Algorithm ◽  
Setup Times ◽  
Flexible Flowshop ◽  
Sequence Dependent ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Hybrid Flexible Flowshop ◽  
Sequence Dependent Setup Times

Job Shop Scheduling to Meet Due Dates With Consideration to Sequence Dependent Setup Times in a Dynamic Environment

2012 ◽  
Author(s):  
Toru Eguchi ◽  
Katsutoshi Nishi ◽  
Hiroaki Kawai ◽  
Takeshi Murayama
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Dynamic Environment ◽  
Setup Times ◽  
Shop Scheduling ◽  
Sequence Dependent ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

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.

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 ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Flow Shop ◽  
Setup Times ◽  
Flexible Flow Shop ◽  
Local Searches ◽  
Sequence Dependent ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Flexible Flow Shop Scheduling ◽  
Sequence Dependent Setup Times

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.

scholarly journals A Genetic Algorithm for a Two-Machine Flowshop with a Limited Waiting Time Constraint and Sequence-Dependent Setup Times

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ju-Yong Lee
Keyword(s):  
Genetic Algorithm ◽  
Waiting Time ◽  
Computation Time ◽  
Time Constraint ◽  
Setup Times ◽  
Mixed Integer ◽  
Sequence Dependent ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

This study considers a two-machine flowshop with a limited waiting time constraint between the two machines and sequence-dependent setup times on the second machine. These characteristics are motivated from semiconductor manufacturing systems. The objective of this scheduling problem is to minimize the total tardiness. In this study, a mixed-integer linear programming formulation was provided to define the problem mathematically and used to find optimal solutions using a mathematical programming solver, CPLEX. As CPLEX required a significantly long computation time because this problem is known to be NP-complete, a genetic algorithm was proposed to solve the problem within a short computation time. Computational experiments were performed to evaluate the performance of the proposed algorithm and the suggested GA outperformed the other heuristics considered in the study.

Sign in / Sign up

Export Citation Format

Share Document