Permutation Flowshop Scheduling in ED Aluminium Using Metaheuristic Approaches
DOI:
https://doi.org/10.14421/jiehis.3003Keywords:
Simulated Annealing, Large Neighbourhood Search, Ant Colony Optimization, Flowshop schedulingAbstract
This study proposes metaheuristics to solve the permutation flowshop scheduling problem in ED Aluminium which produces kitchen utensils. The aim is to find the processing sequence of products that results in the shortest total completion time, minimizing makespan and total flowtime. Three metaheuristics are developed, which are Simulated Annealing (SA), Large Neighborhood Search (LNS), and Ant Colony Optimization (ACO). Experiments are performed in this research to evaluate the three algorithms. The result using the simulated annealing algorithm is considered better because it has a shorter makespan. The contribution of this study is developing Simulated Annealing, Large Neighborhood Search, and Ant Colony Optimization to solve the problem.
References
Isnaini, W. (2016). Minimasi Makespan Penjadwalan Produksi Dengan Metode Palmer, Dannenbring, Dan Campbell Dudek Smith (Cds) Pada Sistem Produksi Flowshop (Studi Kasus: IKM ED Aluminium Yogyakarta). Tesis. Yogyakarta: Universitas Gadjah Mada.
Liantoni, F. (2015). Deteksi Tepi Citra Daun Mangga Menggunakan Algoritma Ant Colony Optimization. Seminar Nasional Sains dan Teknologi Terapan III, Vol. 3, 411-418.
Mohan, B. C. and Baskaran, R. (2012). A survey: Ant Colony Optimization Based Recent Research and Implementation on Several Engineering Domain. Expert System and Application, Vol. 39 No. 4, 4618-4627.
Muharni, Y., Febianti, E., dan Sofa, N. N. (2019). Minimasi Makespan Pada Penjadwalan Flow Shop Mesin Paralel Produk Steel Bridge B-60 Menggunakan Metode. Longest Processing Time Dan Particle Swarm Optimization. Jurnal Industrial Services, Vol. 4. No. 2.
Nurdiansyah, R. (2011). Pengembangan Algoritma Differential Evolution Untuk Penjadwalan Flow Shop Multi Obyektif Dengan Banyak Mesin. Prosiding Konferensi Nasional Inovasi dalam Desain dan Teknologi.
Rachmawati, N. L. and Lentari, M. (2022). Penerapan Metode Min-Max untuk Minimasi Stockout dan Overstock Persediaan Bahan Baku. Jurnal INTECH, Vol. 8. No. 2.
Redi, A. A. N. P. and Redioka, A. A. N. A. (2019). Algoritma Simulated Annealing untuk Optimasi Rute Kendaraan dan Pemindahan Lokasi Sepeda pada Sistem Public Bike Sharing. Jurnal Sistem dan Manajemen Industri. Vol. 3 No. 1, 50-58.
Widodo, D. S., Santoso, P. B., and Siswanto, E. (2014). Pendekatan Algoritma Cross Entropy-Genetic Algorithm Untuk Menurunkan Makespan Pada Penjadwalan Flow Shop. JEMIS (Journal of Engineering & Management in Industrial System), Vol 2 No. 1.
Winarno and Redi, A. A. N. P. (2020). Analisa Perbandingan Metode Simulated Annealing dan Large Neighborhood Search Untuk Memecahkan Masalah Lokasi dan Rute Kendaraan Dua Eselon. Jurnal Manajemen Industri dan Logistik, Vol. 4 No. 1, 35-46.
Widyaningsih, R. R., Sulistyo, B., and Astuti, M. D. (2018). Perbaikan Penjadwalan Aktivasi Starter Pack Untuk Meminimasi Keterlambatan Dengan Menggunakan Metode Earliest Due Date Pada PT XYZ. JATI UNIK: Jurnal Ilmiah Teknik dan Manajemen Industri, Vol. 1 No. 2, 60-69.
Nurdiansyah, R. (2011). Pengembangan algoritma differential evolution untuk penjadwalan flow shop multi obyektif dengan banyak mesin. Prosiding Konferensi Nasional “Inovasi dalam Desain dan Teknologi”.
Rifai, A. P., Kusumastuti, P. A., Mara, S. T. W., Norcahyo, R., and Dawal, S. Z. (2021). Multi-operator hybrid genetic algorithm-simulated annealing for reentrant permutation flow-shop scheduling. ASEAN Engineering Journal, Vol. 11 No. 3, 109-126.
Kusumaningsih, D. A., Azim, A. F., Albab, D. A. I. U., Hans, F. R., Korin, F., Pohan, R. N. A. M., Ananta, V. S., and Rifai, A. P. (2022). Simulated Annealing untuk Perancangan Tata Letak Industri Furniture dengan Model Single dan Double Row Layout. Jurnal Media Teknik Dan Sistem Industri, Vol. 6 No. 1, 60-67.
Agista, A. B., Natuna, A. P., Wangsa, H. B., Fernanda, J., Akmal, N. N., and Rifai, A. P. (2021). Perancangan Tata Letak Fasilitas UKM Kerajinan Kayu Dengan Metode Simulated Annealing. Journal of Industrial and Manufacture Engineering, Vol. 5 No. 2, 137-147.
Fathollahi-Fard, A. M., Govindan, K., Hajiaghaei-Keshteli, M., and Ahmadi, A. (2019). A green home health care supply chain: New modified simulated annealing algorithms. Journal of Cleaner Production, Vol. 240, 118200.
Rifai, A. P., Nguyen, H. T., and Dawal, S. Z. M. (2016). Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling. Applied Soft Computing, Vol. 40, 42-57.
Rifai, A. P., Mara, S. T. W., and Sudiarso, A. (2021). Multi-objective distributed reentrant permutation flow shop scheduling with sequence-dependent setup time. Expert Systems with Applications, Vol. 183, 115339.
Mara, S. T. W., Rifai, A. P., dan Sopha, B. M. 2022. An adaptive large neighborhood search heuristic for the flying sidekick traveling salesman problem with multiple drops. Expert Systems with Applications, Vol. 205, 117647.
Rifai, A. P., Sutoyo, E., Mara, S. T. W., and Dawal, S. Z. M. (2022). Multiobjective Sequence-Dependent Job Sequencing and Tool Switching Problem. IEEE Systems Journal, Vol. 17 No. 1, 1395-1406.
Rokbani, N., Kumar, R., Abraham, A., Alimi, A. M., Long, H. V., Priyadarshini, I., and Son, L. H. (2021). Bi-heuristic ant colony optimization-based approaches for traveling salesman problem. Soft Computing, Vol. 25, 3775-3794.
Deng, W., Xu, J., and Zhao, H. (2019). An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem. IEEE access, Vol. 7, 20281-20292.
Kurdi, M. (2022). Ant colony optimization with a new exploratory heuristic information approach for open shop scheduling problem. Knowledge-Based Systems, Vol. 242, 108323.
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