OPTIMASI MAKESPAN DAN TOTAL TARDINESS DALAM PENJADWALAN MESIN PRODUKSI TYPE FLOW SHOP MENGGUNAKAN METODE NON-DOMINATED SORTING GENETIC ALGORITHM (NSGA-II)

Fifin Sonata, Muhammad Zarlis, Tulus Tulus

Abstract

Permasalahan optimasi dua objek yaitu makespan dan total tardiness pada penjadwalan mesin produksi flow shop berkaitan dengan penyusunan penjadwalan mesin secara teratur. Optimasi kedua permasalahan tersebut merupakan optimasi yang bertolak belakang sehingga diperlukan motode optimasi multi-objective A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimazitaion : NSGA-II yang dapat mengintegrasikan permasalahan tersebut. Penyelesaian penjadwalan mesin produksi flow shop dengan algoritma NSGA-II mampu membangun jadwal dengan meminimalkan makespan dan total tardiness. NSGA-II dapat membantu memberikan solusi penjadwalan mesin produksi flow shop yang efisien berupa solusi pareto optimal yang dapat memberikan sekumpulan solusi alternatif bagi pengambil keputusan dalam membuat penjadwalan mesin produksi yang diharapkan. Nilai solusi yang diperoleh akan terlihat dengan cara melakukan perbandingan antara dominasi solusi Aggregat Of Function (AOF) dengan solusi NSGA-II.

Keywords


Makespan; NSGA-II; Penjadwalan; Tardiness

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References

Deb, K. & Tiwari, S. 2008. Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization. European Journal of Operational Research 185 (2008) 1062–1087. Elsevier.

Lemesre, L., Dhaenens, C. & Talbi, E.G. 2005. An Exact Parallel Method For A Bi-objective Permutation Flowshop Problem. Elsevier Science. 8 April 2005.

Gajpal, Y., Dua, A. & Sahu, S.N. 2014. Heuristics for single machine scheduling under competition to minimize total weighted completion time and makespan objectives. International Conference on Applied Operational Research, Proceedings.

Balasundaram, R., Valavan, D. & Baskar, N. 2014. Heuristic Based Approach for BI-Criteria Optimization of Minimizing Makespan and Total Flow Time of Flowshop Scheduling. International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:14 No:02.

Rajendran, C. & Ziegler, Hans. 2004. Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs. European Journal of Operational Research 155 (2004) 426–438. Elsevier.

Jozefowiez, N., Semet, F. & Talbi, E. 2008. Multi-objective vehicle routing problems. European Journal of Operational Research 189 (2008) 293–309. Elsevier.

Mishra, S.K., Panda, G. & Meher, S. 2009. Comparative Performance Evaluation of Multiobjective Optimization Algorithm For Portfolio Management. Presented International Symposium on Biologically Inspired Computing and Application (BICA-2009). Bhubaneswar, India. December 2009.

Minella, G., Ruiz, R. & Ciavotta, M. 2007. A review and evaluation of multi-objective algorithms for the flowshop scheduling problem. Grupo de Sistemas de Optimización Aplicada. 29 Maret 2007

Santosa, B. & Rofiq, A. 2014. The Development of Simulated Annealing Algorithm for Hybrid Flow shop Scheduling Problem to Minimize Makespan and Total Tardiness. Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management. Bali, Indonesia, January 7 – 9, 2014.

Ginting, R. 2009. Penjadwalan Mesin. Graha Ilmu. Yogyakarta.

Deb, K. 2011. Multi-Objective Optimization Using Evolutionary Algorithms: An Introduction. Department of Mechanical Engineering Indian Institute of Technology Kanpur, PIN 208016, India. KanGAL Report Number 2011003. Springer

Srinivas, N. dan Deb, K. 1994, Multiobjective Optimization using Non-Dominated Sorting in Genetic Algorithms, Evolutionary Computation Journal, Vol. 2 No. 3.

Deb, K., Pratap, A. & Meyarivan, T. 2002. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 6, NO. 2, APRIL 2002.

Zitzler, E. & Thiele, L. 1998. Multiobjective Optimization Using Evolutionary Algorithms-A Comparative Case Study. Parallel Problem Solving from Nature PPSN V Amsterdam. Page 292 301. Springer

Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C. M. & Fonseca, G. 2002. Performance Assessment of Multiobjective Optimizers: An Analysis and Review. TIK-Report No. 139. Institut f¨ur Technische Informatik und Kommunikationsnetze, ETH Z¨urich Gloriastrasse 35, ETH-Zentrum, CH–8092 Z¨urich, Switzerland.


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