TY - JOUR
T1 - Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking
AU - Abu Doush, Iyad
AU - Al-Betar, Mohammed Azmi
AU - Awadallah, Mohammed A.
AU - Alyasseri, Zaid Abdi Alkareem
AU - Makhadmeh, Sharif Naser
AU - El-Abd, Mohammed
N1 - Abu Doush, I., Al-Betar, M. A., Awadallah, M. A., Alyasseri, Z. A. A., Makhadmeh, S. N., & El-Abd, M. (2022). Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking. Swarm and Evolutionary Computation, 74, 101127. https://doi.org/10.1016/j.swevo.2022.101127i.org/10.1016/j.swevo.2022.101127
PY - 2022/10
Y1 - 2022/10
N2 - This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then the harmony search algorithm iterates to look for and to develop a new solution enhanced by using neighboring heuristics. A migration process is applied, after a predefined number of iterations, to perform an exchange between some individuals in islands. The proposed algorithm is evaluated using 12 real-world datasets, each with 10 instances. A sensitivity analysis of the island model parameters is conducted to choose values that minimize the total flow time. The evaluation is conducted using two criteria, the number of evolutions and the Central Processing Unit (CPU) time using six comparative methods and sixteen comparative methods, respectively. For the first criterion, the proposed algorithm excels other comparative algorithms when solving instances of four datasets. For the second criterion, the proposed algorithm outperforms other comparative methods in six out of the twelve datasets. In conclusion, The obtained results prove the efficiency and competitiveness of the proposed algorithm when tackling the blocking flow-shop scheduling problem.
AB - This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then the harmony search algorithm iterates to look for and to develop a new solution enhanced by using neighboring heuristics. A migration process is applied, after a predefined number of iterations, to perform an exchange between some individuals in islands. The proposed algorithm is evaluated using 12 real-world datasets, each with 10 instances. A sensitivity analysis of the island model parameters is conducted to choose values that minimize the total flow time. The evaluation is conducted using two criteria, the number of evolutions and the Central Processing Unit (CPU) time using six comparative methods and sixteen comparative methods, respectively. For the first criterion, the proposed algorithm excels other comparative algorithms when solving instances of four datasets. For the second criterion, the proposed algorithm outperforms other comparative methods in six out of the twelve datasets. In conclusion, The obtained results prove the efficiency and competitiveness of the proposed algorithm when tackling the blocking flow-shop scheduling problem.
KW - Flow shop problem
KW - Harmony search algorithm
KW - Heuristics
KW - Island model
KW - Optimization
KW - Scheduling
KW - Structured population
UR - http://www.scopus.com/inward/record.url?scp=85134757390&partnerID=8YFLogxK
U2 - 10.1016/j.swevo.2022.101127
DO - 10.1016/j.swevo.2022.101127
M3 - Article
SN - 2210-6502
VL - 74
JO - Swarm and Evolutionary Computation
JF - Swarm and Evolutionary Computation
M1 - 101127
ER -