No-Wait Flowshop Permutation Scheduling Problem : Fire Hawk Optimizer Vs Beluga Whale Optimization Algorithm

Muhammad Aghniya Baihaqi(1*), Dana Marsetiya Utama(2),

(1) Universitas Muhammadiyah Malang
(2) Universitas Muhammadiyah Malang
(*) Corresponding Author
DOI: https://doi.org/10.23917/jiti.v22i1.21128

Abstract

No-Wait Flowshop Permutation Scheduling Problem (NWPFSP) is a scheduling problem that states that every job completed on machine n must be processed immediately on the next machine. The NWPFSP problem is an extension of the flowshop problem. This article proposes two new algorithms fire hawk optimization and beluga whale optimization, to solve the NWPFSP problem and minimize makespan. The two new algorithms developed to solve the NWPFSP problem are tested on three different cases. Each algorithm was run 30 times and was compared using an independent sample t-test. The results were also compared with the Campbell Dudek Smtih algorithm. In addition, the effectiveness of the FHO and BWO algorithms was assessed against the CDS algorithm using the Relative Error Percentage (REP) method. The results show that the FHO and BWO algorithms are better at solving NWPFSP problems when compared to the CDS algorithm. However, the BWO algorithm is more recommended in cases with large data because it can provide better results.

Keywords

Fire hawk optimizer; Beluga Whale Optimization; No-Wait Flowshop,;Scheduling

Full Text:

PDF

References

Azizi, M., Talatahari, S., & Gandomi, A. H. (2022). Fire Hawk Optimizer: a novel metaheuristic algorithm. Artificial Intelligence Review, 1-77.

Baker, K. R., & Trietsch, D. (2009). Safe scheduling: Setting due dates in single-machine problems. European Journal of Operational Research, 196(1), 69-77.

Baker, K. R., & Trietsch, D. (2013). Principles of sequencing and scheduling: John Wiley & Sons.

Bertolissi, E. (2000). Heuristic algorithm for scheduling in the no-wait flow-shop. Journal of Materials Processing Technology, 107(1-3), 459-465.

Carlier, J. (1978). Ordonnancements à contraintes disjonctives. RAIRO-Oper. Res., 12(4), 333-350.

Ding, J., Song, S., Zhang, R., Gupta, J. N. D., & Wu, C. (2015). Accelerated methods for total tardiness minimisation in no-wait flowshops. International Journal of Production Research, 53(4), 1002-1018.

Engin, O., & Güçlü, A. (2018). A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems. Applied Soft Computing, 72, 166-176.

Firmansyah, A., Utomo, D., & Irawan, M. (2016). Algoritma Genetika Ddengan Modifikasi Kromosom Untuk Penyelesaian Masalah Penjadwalan Flowshop. J. Sain dan Seni, 1(1).

Grabowski, J., & Pempera, J. (2005). Some local search algorithms for no-wait flow-shop problem with makespan criterion. Computers & Operations Research, 32(8), 2197-2212.

Guevara-Guevara, A., Gómez-Fuentes, V., Posos-Rodríguez, L., Remolina-Gómez, N., & González-Neira, E. (2022). Earliness/tardiness minimization in a no-wait flow shop with sequence-dependent setup times. Journal of Project Management, 7(3), 177-190.

Hernanda, D. A., & Hariastuti, N. L. P. (2022). Usulan Penjadwalan Produksi Pada Departemen Produksi PT. Preshion Engineering Plastec.

Iqbal, P. (2014). Genetic Algorithm for Permutation Flowshop Scheduling Problem to Minimize the Makespan. International Journal of Computing Algorithm, 3, 1086-1091. doi:10.20894/IJCOA.101.003.002.021

Li, X., & Yin, M. (2013). An opposition-based differential evolution algorithm for permutation flow shop scheduling based on diversity measure. Advances in Engineering Software, 55, 10-31.

Makuchowski, M. (2015). Permutation, no-wait, no-idle flow shop problems. Archives of Control Sciences(2).

Mantegna, R. N. (1994). Fast, accurate algorithm for numerical simulation of Levy stable stochastic processes. Physical Review E, 49(5), 4677.

McMillan, J. H., & Schumacher, S. (2010). Research in Education: Evidence-Based Inquiry, MyEducationLab Series. Pearson.

Nadia, V., Dewi, D. R. S., & Sianto, M. E. (2017). Penjadwalan Produksi dan Perancangan Persediaan Bahan Baku di PT. Wahana Lentera Raya. Widya Teknik, 9(2), 179-192.

Nailwal, K., Gupta, D., & Jeet, K. (2016). Heuristics for no-wait flow shop scheduling problem. International Journal of Industrial Engineering Computations, 7(4), 671-680.

Pan, Q.-K., Wang, L., & Qian, B. (2009). A novel differential evolution algorithm for bi-criteria no-wait flow shop scheduling problems. Computers & Operations Research, 36(8), 2498-2511.

Pan, Q.-K., Wang, L., & Zhao, B.-H. (2008). An improved iterated greedy algorithm for the no-wait flow shop scheduling problem with makespan criterion. The International Journal of Advanced Manufacturing Technology, 38(7), 778-786.

Pinedo, M. L. (2012). Scheduling (Vol. 29): Springer.

Pinedo, M. L. (2016). Scheduling: Theory, Algorithms, and Systems, Springer International Publishing.

Raaymakers, W. H. M., & Hoogeveen, J. A. (2000). Scheduling multipurpose batch process industries with no-wait restrictions by simulated annealing. European Journal of Operational Research, 126(1), 131-151.

Rajendran, C. (1994). A no-wait flowshop scheduling heuristic to minimize makespan. Journal of the Operational Research Society, 45(4), 472-478.

Reeves, C. R. (1995). A genetic algorithm for flowshop sequencing. Computers & Operations Research, 22(1), 5-13. doi:https://doi.org/10.1016/0305-0548(93)E0014-K

Shishehgarkhaneh, M. B., Azizi, M., Basiri, M., & Moehler, R. C. (2022). BIM-Based Resource Tradeoff in Project Scheduling Using Fire Hawk Optimizer (FHO). Buildings, 12(9). doi:10.3390/buildings12091472

Utama, D. M. (2021). Minimizing Number of Tardy Jobs in Flow Shop Scheduling Using A Hybrid Whale Optimization Algorithm.

Utama, D. M., Widodo, D. S., Ibrahim, M. F., & Dewi, S. K. (2020). A new hybrid butterfly optimization algorithm for green vehicle routing problem. Journal of Advanced Transportation, 2020.

Wismer, D. A. (1972). Solution of the flowshop-scheduling problem with no intermediate queues. Operations research, 20(3), 689-697.

Ye, H., Li, W., & Miao, E. (2016). An effective heuristic for no-wait flow shop production to minimize makespan. Journal of Manufacturing Systems, 40, 2-7.

Zhong, C., Li, G., & Meng, Z. (2022). Beluga whale optimization: A novel nature-inspired metaheuristic algorithm. Knowledge-Based Systems, 109215.

Article Metrics

Abstract view(s): 325 time(s)
PDF: 243 time(s)

Refbacks

  • There are currently no refbacks.