An adaptive learning approach for no-wait flowshop scheduling problems to minimize make-span
- https://doi.org/10.2991/ijcis.2011.4.4.11How to use a DOI?
- No-wait flowshop; Adaptive learning approach; Genetic algorithm; Makespan
No-wait flowshop scheduling problem (NW-FSSP) with the objective to minimize the makespan is an important sequencing problem in the production plans and applications of no-wait flowshops can be found in several industries. In a NW-FSSP, jobs are not allowed to wait between two successive machines. The NW-FSSPs are addressed to minimize makespan and the NW-FSSP is known as a NP- Hard problem. In this study, Agarwal et al.â€™s1 adaptive learning approach (ALA) is improvement for NW-FSSPs. Improvements in adaptive learning approach is similar to neural-network training. The improvement adaptive learning approach (IALA) is applied to all of the 192 problems. The proposed IALA method for NW-FSSP is compared with Aldowaisan and Allahverdiâ€™s2 results by using Genetic heuristic. The results of computational experiments on randomly generated NW-FSSPs are show that the proposed adaptive learning approach performs quite well.
- © 2011, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Orhan Engin AU - Cengiz Gunaydin PY - 2011 DA - 2011/06/01 TI - An adaptive learning approach for no-wait flowshop scheduling problems to minimize make-span JO - International Journal of Computational Intelligence Systems SP - 521 EP - 529 VL - 4 IS - 4 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2011.4.4.11 DO - https://doi.org/10.2991/ijcis.2011.4.4.11 ID - Engin2011 ER -