The Flowshop Scheduling Makespan by the ACO-GA Algorithm The Flowshop Scheduling Makespan by the ACO-GA Algorithm
Main Article Content
Abstract
Flow shop scheduling could be a scheduling model where all jobs that are processed flow within the same direction / path. the matter is usually faced if n jobs are processed on m machines, where what must be done first and what allocates jobs on the machine in order that a scheduled production process are obtained. To validate this algorithm a computational test was done employing a dataset of 60 examples from the Taillard Benchmark. HS algorithm with a comparison of two constructive heuristics from the literature, namely the NEH heuristic and stochastic greedy heuristic (SG). The average results obtained for dataset sizes are 20 x 5 to 50 x 10, that the ACO-GA algorithm has smaller makespan compared to the opposite two algorithms, except for large dataset sizes the ACO-GA algorithm has larger makespan compared to the 2 algorithms above with difference of 1.4 units of your time
Downloads
Article Details
[2] Blum, C. 2005. AntColony Optimization: Introduction And Recent Trends. Physics of Life Reviews 2. 354-371
[3] Bulbul, K., Kaminsky, P., Yano, C. 2003. Flow Shop Scheduling with Earliness, Tardiness, and Intermediate Inventory Holding Costs. Naval Research Logistics Journal. 407-444
[4] Zini, H & ElBernoussi, S. 2016. A Modified Harmony Search for Flow Shop Scheduling Problem. Laboratory of Mathematics, Computer Science and Applications Mohammed V University in Rabat Morocco.
[5] Kora, P. & Yadlapalli, P. 2017. Crossover Operators in Genetic Algorithms: A Review. International Journal of Computer Applications 162(10) : 34 – 36.
[6] Zukhri, Z & Paputungan, I. V. 2013. A Hybrid Optimization Algorithm Based On Genetic Algorithm And Ant Colony Optimization. International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 4, No. 5, September 2013. Faculty of Industrial Technology, Islamic University of Indonesia.
[7] Rahman, H., Sarker, R. & Essam, D. (Student Member, IEEE) 2013. Permutation Flow Shop Scheduling with Dynamic Job Order Arrival. International Journal University of New South Wales, Canberra, Australia
[8] Ali, A. G. & Espinouse, M. L. 2015. A Two-Machine Flow-Shop Scheduling With A Deteriorating Maintenance Activity On The Second Machine. presented at the 6th IESM Conference, October 2015, Seville, Spain. Univ. Grenoble Alpes, Grenoble, France.
[9] Ta, Q. C, Billaut, J. C & Bouquard, J. L. 2015. Heuristic Algorithms To Minimize The Total Tardiness In A Flow Shop Production And Outbound Distribution Scheduling Problem. presented at the 6th IESM Conference, October 2015, Seville, Spain.
[9] Zhang, X. Y. & Chen, L. 2016. Heuristics for Minimizing the Total Tardiness in a Re-Entrant Hybrid Flow Shop With Non-Identical Machines in Parallel. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.
[10] Modrák, V & Pandian, R. S. 2012. Flow Shop Scheduling Algorithm To Minimize Completion Time FOR n-JOBS m-Machines Problem. IEEE International Journal.ISSN 1330-3651.
[11] Yang, W & Wang, M. 2014. Research on Hybrid Flow Shop Scheduling Using Ant Colony Algorithm Based on Petri Nets. IEEE Journal. School of Information Engineering, Guangdong University of Technology.
[12] Ta, Q. C, Billaut, J. C & Bouquard, J. L. 2015. Heuristic Algorithms To Minimize The Total Tardiness In A Flow Shop Production And Outbound Distribution Scheduling Problem. The 6th IESM Conference, October 2015, Seville, Spain.
[13] Rajendran, C. & Ziegler, H. 2013. Ant Colony Algorithms For Permutation Flowshop Scheduling To Minimize Makespan/Total Flowtime Of Jobs. European Journal of Operational Research.