Algoritma ant-lion optimizer untuk meminimasi emisi karbon pada penjadwalan flow shop dependent sequence set-up

Dana Marsetiya Utama, Teguh Baroto, Dewi Maharani, Fathiha Raudhatul Jannah, Ricca Andhini Octaria


Industri manufaktur akhir-akhir ini dituntut untuk memperhatikan isu lingkungan. Pemakaian energi pada produksi umumnya menghasilkan emisi karbon. Emisi karbon ini menjadi permasalahan di lingkungan. Untuk mengurangi pemakaian emisi karbon, penelitian ini menggabungkan metode penjadwalan dan emisi karbon sebagai solusi dalam masalah lingkungan. Kasus pada artikel ini adalah flow shop dependent sequence set-up. Jurnal ini mengusulkan algoritma baru Ant Lion Optimizer (ALO) yang terinspirasi oleh alam untuk meminimasi emisi karbon. Beberapa percobaan numerik dilakukan untuk mengetahui parameter terbaik dari Algoritma ALO. Untuk menguji keefektifan dari algoritma, Algoritma ALO ini dibandingkan dengan beberapa algoritma populer saat ini. Hasil percobaan numerik menunjukan algoritma ALO efektif untuk meminimasi emisi karbon.


Manufacture industry recently is required to pay attention of enviromental issue. The use of energy in production generally produces carbon emissions. This carbon emission is a problem in the environment. This study combines scheduling methods and carbon emissions as a solution to environmental issues to reduce the use of carbon emissions. The case in this article is the flow shop dependent sequence set-up. This journal proposes a new Ant Lion Optimizer (ALO) algorithm inspired by nature to minimize carbon emissions. Several numerical experiments were conducted to determine the best parameters of the ALO algorithm. This ALO algorithm is compared with several popular algorithms today. The numerical experiment results show that the ALO algorithm is useful for minimizing carbon emissions.


ant lion optimization; penjadwalan; flow shop; dependent sequence setup; emisi karbon

Full Text:

PDF (Indonesian)


Ding, J.-Y., Song, S. & Wu, C. 2016. Carbon-efficient scheduling of flow shops by multi-objective optimization. European Journal of Operational Research, 248, 758-771.

Du, Z. & Lin, B. 2018. Analysis of carbon emissions reduction of China's metallurgical industry. Journal of Cleaner Production, 176, 1177-1184.

Elias, R., Yuan, M., Wahab, M. & Patel, N. 2019. Quantifying saving and carbon emissions reduction by upgrading residential furnaces in Canada. Journal of Cleaner Production, 211, 1453-1462.

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.

Fang, K., Uhan, N., Zhao, F. & Sutherland, J. W. 2011. A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction. Journal of Manufacturing Systems, 30, 234-240.

Firdaus, M., Masudin, I. & Utama, D. M. 2015. Penjadwalan flow shop dengan menggunakan simulated annealing. Spektrum Industri, 13.

Galinato, G. I. & Yoder, J. K. 2010. An integrated tax-subsidy policy for carbon emission reduction. Resource and Energy Economics, 32, 310-326.

Garside, A. K., Utama, D. M. & Arifin, M. R. Penjadwalan produksi flow shop menggunakan algoritma branch and bound untuk meminimasi mean tardiness. Prosiding SENTRA (Seminar Teknologi dan Rekayasa), 2018.

Harto, S., Garside, A. K. & Utama, D. M. 2016. Penjadwalan produksi menggunakan algoritma jadwal non delay untuk meminimalkan makespan studi kasus di cv. Bima mebel. Spektrum Industri, 14.

Husen, M., Masudin, I. & Utama, D. M. 2015. Penjadwalan job shop statik dengan metode simulated annealing untuk meminimasi waktu makespan. Spektrum Industri, 13.

Jain, M., Singh, V. & Rani, A. 2018. A novel nature-inspired algorithm for optimization: Squirrel search algorithm. Swarm and Evolutionary Computation.

Liu, Q., Zhan, M., Chekem, F. O., Shao, X., Ying, B. & Sutherland, J. W. 2017. A hybrid fruit fly algorithm for solving flexible job-shop scheduling to reduce manufacturing carbon footprint. Journal of Cleaner Production, 168, 668-678.

Ma, X., Wang, C., Dong, B., Gu, G., Chen, R., Li, Y., Zou, H., Zhang, W. & Li, Q. 2019. Carbon emissions from energy consumption in China: Its measurement and driving factors. Science of the total environment, 648, 1411-1420.

Masudin, I., Utama, D. M. & Susastro, F. 2014. Penjadwalan flow shop menggunakan algoritma nawaz enscore ham.

Mirjalili, S. 2015. The ant lion optimizer. Advances in Engineering Software, 83, 80-98.

Nasution, R., Garside, A. K. & Utama, D. M. 2017. Penjadwalan job shop dengan pendekatan algoritma artificial immune system. Jurnal Teknik Industri, 18, 29-42.

Nguyen, D. C. H., Ascough Ii, J. C., Maier, H. R., Dandy, G. C. & Andales, A. A. 2017. Optimization of irrigation scheduling using ant colony algorithms and an advanced cropping system model. Environmental Modelling & Software, 97, 32-45.

Pan, Q.-K., Gao, L., Li, X.-Y. & Gao, K.-Z. 2017. Effective metaheuristics for scheduling a hybrid flow shop with sequence-dependent setup times. Applied Mathematics and Computation, 303, 89-112.

Piroozfard, H., Wong, K. Y. & Wong, W. P. 2018. Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm. Resources, Conservation and Recycling, 128, 267-283.

Tian, W., He, M., Guo, W., Huang, W., Shi, X., Shang, M., Toosi, A. N. & Buyya, R. 2018a. On minimizing total energy consumption in the scheduling of virtual machine reservations. Journal of Network and Computer Applications, 113, 64-74.

Tian, Y., Xiong, S., Ma, X. & Ji, J. 2018b. Structural path decomposition of carbon emission: A study of China's manufacturing industry. Journal of Cleaner Production, 193, 563-574.

Umamaheswari, E., Ganesan, S., Abirami, M. & Subramanian, S. 2017. Cost Effective Integrated Maintenance Scheduling in Power Systems using Ant Lion Optimizer. Energy Procedia, 117, 501-508.

Utama, D. M. 2017. Analisa perbandingan penggunaan aturan prioritas penjadwalan pada penjadwalan non delay n job 5 machine. Research Report, 1.

Utama, D. M. 2018. Pengembangan algoritma NEH Dan CDS Untuk meminimasi consumption energy pada penjadwalan flow shop Prosiding SENTRA (Seminar Teknologi dan Rekayasa), 2018 Malang. Malang: Universitas Muhammadiyah Malang.

Utama, D. M. 2019. An effective hybrid sine cosine algorithm to minimize carbon emission on flow-shop scheduling sequence dependent setup. 2019, 20, 10.

Utama, D. M., Widodo, D. S., Wicaksono, W. & Ardiansyah, L. R. 2019. A new hybrid metaheuristics algorithm for minimizing energy consumption in the flow shop scheduling problem. International Journal of Technology, 10, 320-331.

Wu, C.-C., Chen, J.-Y., Lin, W.-C., Lai, K., Liu, S.-C. & Yu, P.-W. 2018. A two-stage three-machine assembly flow shop scheduling with learning consideration to minimize the flowtime by six hybrids of particle swarm optimization. Swarm and Evolutionary Computation.

Xu, J., Wang, F., Lv, C. & Xie, H. 2018. Carbon emission reduction and reliable power supply equilibrium based daily scheduling towards hydro-thermal-wind generation system: A perspective from China. Energy Conversion and Management, 164, 1-14.

Yu, C., Semeraro, Q. & Matta, A. 2018. A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility. Computers & Operations Research, 100, 211-229.

Zhang, Y., Liu, Q., Zhou, Y. & Ying, B. 2017. Integrated optimization of cutting parameters and scheduling for reducing carbon emissions. Journal of Cleaner Production, 149, 886-895.



  • There are currently no refbacks.

Our journal indexed by:

Copyright © Baristand Industri Padang, 2015. Powered By OJS

Theme design credited to MEV edited by JLI

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License