An immunity-based hybrid genetic algorithms for permutation flowshop scheduling problems

2015 ◽  
Vol 85 (9-12) ◽  
pp. 2459-2469 ◽  
Author(s):  
Malika Bessedik ◽  
Fatima Benbouzid-Si Tayeb ◽  
Hamza Cheurfi ◽  
Ammar Blizak
2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Rong-Chang Chen ◽  
Jeanne Chen ◽  
Tung-Shou Chen ◽  
Chien-Che Huang ◽  
Li-Chiu Chen

The permutation flowshop scheduling problem (PFSP) is an important issue in the manufacturing industry. The objective of this study is to minimize the total completion time of scheduling for minimum makespan. Although the hybrid genetic algorithms are popular for resolving PFSP, their local search methods were compromised by the local optimum which has poorer solutions. This study proposed a new hybrid genetic algorithm for PFSP which makes use of the extensive neighborhood search method. For evaluating the performance, results of this study were compared against other state-of-the-art hybrid genetic algorithms. The comparisons showed that the proposed algorithm outperformed the other algorithms. A significant 50% test instances achieved the known optimal solutions. The proposed algorithm is simple and easy to implement. It can be extended easily to apply to similar combinatorial optimization problems.


2012 ◽  
Vol 39 (7) ◽  
pp. 1450-1457 ◽  
Author(s):  
Shih-Hsin Chen ◽  
Pei-Chann Chang ◽  
T.C.E. Cheng ◽  
Qingfu Zhang

2006 ◽  
Vol 33 (6) ◽  
pp. 1540-1556 ◽  
Author(s):  
Julien Fondrevelle ◽  
Ammar Oulamara ◽  
Marie-Claude Portmann

Sign in / Sign up

Export Citation Format

Share Document