Energy-Aware Scheduling in Hybrid Flow Shop using Firefly Algorithm

Authors

  • Ahmed Nedal Abid Al Kareem Jabari Department of Mechanical Engineering, Palestine Polytechnic University, Hebron, Palestine
  • Afif Hasan Department of Mechanical Engineering, Palestine Polytechnic University, Hebron, Palestine

DOI:

https://doi.org/10.22219/JTIUMM.Vol22.No1.18-30

Keywords:

Hybrid Flow Shop, Scheduling, Firefly Algorithm, Energy consumption

Abstract

Nowadays, the industrial sector takes up a significant portion of the world's total energy consumption. This sector is responsible for half of the total energy consumed in the world. Therefore, efficiency in the industrial sector becomes an essential issue. One of the main factors triggering the high energy consumption in this sector is that many machines are left idle. Idle machines during the manufacturing process require electricity and other energies. This research aimed to develop a firefly algorithm that can minimize the energy consumption in the hybrid flow shop scheduling problem. This algorithm is used to determine the optimum order of the jobs. The ultimate goal is to minimize energy consumption. The experiment on the algorithm was conducted by employing iteration and population variations. The research results show that population and iteration affect the quality of the hybrid flow shop scheduling solution.

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References

S. Schulz, J. S. Neufeld, and U. Buscher, "A multi-objective iterated local search algorithm for comprehensive energy-aware hybrid flow shop scheduling," Journal of Cleaner Production, vol. 224, pp. 421-434, 2019. https://doi.org/10.1016/j.jclepro.2019.03.155.

D. M. Utama, "An effective hybrid sine cosine algorithm to minimize carbon emission on flow-shop scheduling sequence dependent setup," Jurnal Teknik Industri, vol. 20, pp. 62-72, 2019. https://doi.org/10.22219/JTIUMM.Vol20.No1.62-72.

G.-S. Liu, Y. Zhou, and H.-D. Yang, "Minimizing energy consumption and tardiness penalty for fuzzy flow shop scheduling with state-dependent setup time," Journal of Cleaner Production, vol. 147, pp. 470-484, 2017. https://doi.org/10.1016/j.jclepro.2016.12.044.

S. Wang, X. Wang, F. Chu, and J. Yu, "An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production," International Journal of Production Research, vol. 58, pp. 2283-2314, 2020. https://doi.org/10.1080/00207543.2019.1624857.

D. M. Utama, T. Baroto, and D. S. Widodo, "Energy-Efficient Flow Shop Scheduling Using Hybrid Grasshopper Algorithm Optimization," Jurnal Ilmiah Teknik Industri, vol. 19, pp. 30-38, 2020. https://doi.org/10.23917/jiti.v19i1.10079.

M. Akbar and T. Irohara, "Scheduling for sustainable manufacturing: A review," Journal of Cleaner Production, vol. 205, pp. 866-883, 2018. https://doi.org/10.1016/j.jclepro.2018.09.100.

M. Li, D. Lei, and J. Cai, "Two-level imperialist competitive algorithm for energy-efficient hybrid flow shop scheduling problem with relative importance of objectives," Swarm and Evolutionary Computation, vol. 49, pp. 34-43, 2019. https://doi.org/10.1016/j.swevo.2019.05.006.

J.-q. Li, H.-y. Sang, Y.-y. Han, C.-g. Wang, and K.-z. Gao, "Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions," Journal of Cleaner Production, vol. 181, pp. 584-598, 2018. https://doi.org/10.1016/j.jclepro.2018.02.004.

C. Yu, Q. Semeraro, and A. Matta, "A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility," Computers & Operations Research, vol. 100, pp. 211-229, 2018. https://doi.org/10.1016/j.cor.2018.07.025.

L. De Felice, "A simulation model for solving the flow shop scheduling problem under uncertainty," 2018.

D. A. Rossit, F. Tohmé, and M. Frutos, "The Non-Permutation Flow-Shop scheduling problem: A literature review," Omega, vol. 77, pp. 143-153, 2018. https://doi.org/10.1016/j.omega.2017.05.010.

D. M. Utama, D. S. Widodo, M. F. Ibrahim, K. Hidayat, T. Baroto, and A. Yurifah, "The hybrid whale optimization algorithm: A new metaheuristic algorithm for energy-efficient on flow shop with dependent sequence setup," in Journal of Physics: Conference Series, 2020, p. 022094. https://doi.org/10.1088/1742-6596/1569/2/022094.

R. Ruiz, Q.-K. Pan, and B. Naderi, "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, vol. 83, pp. 213-222, 2019. https://doi.org/10.1016/j.omega.2018.03.004.

V. Fernandez-Viagas, P. Perez-Gonzalez, and J. M. Framinan, "Efficiency of the solution representations for the hybrid flow shop scheduling problem with makespan objective," Computers & Operations Research, vol. 109, pp. 77-88, 2019. https://doi.org/10.1016/j.cor.2019.05.002.

V. Fernandez-Viagas, J. M. Molina-Pariente, and J. M. Framinan, "New efficient constructive heuristics for the hybrid flowshop to minimise makespan: A computational evaluation of heuristics," Expert Systems with Applications, vol. 114, pp. 345-356, 2018. https://doi.org/10.1016/j.eswa.2018.07.055.

Z. Liu, J. Yan, Q. Cheng, C. Yang, S. Sun, and D. Xue, "The mixed production mode considering continuous and intermittent processing for an energy-efficient hybrid flow shop scheduling," Journal of Cleaner Production, vol. 246, p. 119071, 2020. https://doi.org/10.1016/j.jclepro.2019.119071.

H. Luo, B. Du, G. Q. Huang, H. Chen, and X. Li, "Hybrid flow shop scheduling considering machine electricity consumption cost," International Journal of Production Economics, vol. 146, pp. 423-439, 2013. https://doi.org/10.1016/j.ijpe.2013.01.028.

B. Du, H. Chen, G. Q. Huang, and H. Yang, "Preference vector ant colony system for minimising make-span and energy consumption in a hybrid flow shop," in Multi-objective evolutionary optimisation for product design and manufacturing, ed: Springer, 2011, pp. 279-304. https://doi.org/10.1007/978-0-85729-652-8_9.

X.-r. Tao, J.-q. Li, T.-h. Huang, and P. Duan, "Discrete imperialist competitive algorithm for the resource-constrained hybrid flowshop problem with energy consumption," Complex & Intelligent Systems, vol. 7, pp. 311-326, 2021. https://doi.org/10.1007/s40747-020-00193-w.

L. Xiang, Z. Fengxing, and Z. Xiangping, "Mathematical model and genetic optimization for hybrid flow shop scheduling problem based on energy consumption," in 2008 Chinese Control and Decision Conference, 2008, pp. 1002-1007. https://doi.org/10.1109/CCDC.2008.4597463.

D. Lei, L. Gao, and Y. Zheng, "A novel teaching-learning-based optimization algorithm for energy-efficient scheduling in hybrid flow shop," IEEE Transactions on Engineering Management, vol. 65, pp. 330-340, 2018. https://doi.org/10.1109/TEM.2017.2774281.

L.-L. Zeng, F.-X. Zou, X.-h. Xu, and Z. Gao, "Dynamic scheduling of multi-task for hybrid flow-shop based on energy consumption," in 2009 International Conference on Information and Automation, 2009, pp. 478-482. https://doi.org/10.1109/ICINFA.2009.5204971.

S. Schulz, "A genetic algorithm to solve the hybrid flow shop scheduling problem with subcontracting options and energy cost consideration," in International Conference on Information Systems Architecture and Technology, 2018, pp. 263-273. https://doi.org/10.1007/978-3-319-99993-7_23.

X. L. Ding, J. Zhu, and C. Liu, "Lagrangian Relaxation Algorithms for Hybrid Flow-Shop Scheduling Problems with Energy Saving," Advanced Materials Research, vol. 997, pp. 821-826, 2014. https://doi.org/10.4028/www.scientific.net/AMR.997.821.

L. Meng, C. Zhang, X. Shao, Y. Ren, and C. Ren, "Mathematical modelling and optimisation of energy-conscious hybrid flow shop scheduling problem with unrelated parallel machines," International Journal of Production Research, vol. 57, pp. 1119-1145, 2019. https://doi.org/10.1080/00207543.2018.1501166.

S. Karthikeyan, P. Asokan, S. Nickolas, and T. Page, "A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems," International Journal of Bio-Inspired Computation, vol. 7, pp. 386-401, 2015. https://doi.org/10.1504/IJBIC.2015.073165.

B. Fan, W. Yang, and Z. Zhang, "Solving the two-stage hybrid flow shop scheduling problem based on mutant firefly algorithm," Journal of Ambient Intelligence and Humanized Computing, vol. 10, pp. 979-990, 2019. https://doi.org/10.1007/s12652-018-0903-3.

X.-S. Yang, "Firefly algorithms for multimodal optimization," in International symposium on stochastic algorithms, 2009, pp. 169-178. https://doi.org/10.1007/978-3-642-04944-6_14.

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Published

2021-02-28

How to Cite

Jabari, A. N. A. A. K., & Hasan, A. (2021). Energy-Aware Scheduling in Hybrid Flow Shop using Firefly Algorithm . Jurnal Teknik Industri, 22(1), 18-30. https://doi.org/10.22219/JTIUMM.Vol22.No1.18-30

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