|Table of Contents|

[1] Wei Li, Chen Weida, Yang Ye,. Scheduling optimization problem considering time-of-use tariffsand piece-rate machine maintenance in EAF steelmaking [J]. Journal of Southeast University (English Edition), 2018, (1): 127-134. [doi:10.3969/j.issn.1003-7985.2018.01.018]
Copy

Scheduling optimization problem considering time-of-use tariffsand piece-rate machine maintenance in EAF steelmaking()
Share:

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
Issue:
2018 1
Page:
127-134
Research Field:
Economy and Management
Publishing date:
2018-03-20

Info

Title:
Scheduling optimization problem considering time-of-use tariffsand piece-rate machine maintenance in EAF steelmaking
Author(s):
Wei Li Chen Weida Yang Ye
School of Economics and Management, Southeast University, Nanjing 211189, China
Keywords:
electric arc furnaces steelmaking time-of-use tariffs piece-rate machine maintenance longest processing time-genetic(LPT-gene)algorithm energy saving
PACS:
F273
DOI:
10.3969/j.issn.1003-7985.2018.01.018
Abstract:
An operating schedule of the parallel electric arc furnaces(EAFs)considering both productivity and energy related criteria is investigated. A mathematical model is established to minimize the total completion time and the total electricity cost. This problem is proved to be an NP-hard problem, and an effective solution algorithm, longest processing time-genetic(LPT-gene)algorithm, is proposed. The impacts of varied processing energy consumption and electricity price on the optimal schedules are analyzed. The integrated influence of the different weight values and the variation between the peak price and the trough price on the optimal solution is studied. Computational experiments illustrate that considering the energy consumption costs in production has little influence on makespan; the computational performance of the proposed longest processing time-genetic algorithm is better than the genetic algorithm(GA)in the issue to be studied; considerable reductions in the energy consumption costs can be achieved by avoiding producing during high-energy price periods and reducing the machining energy consumption difference. The results can be a guidance for managers to improve productivity and to save energy costs under the time-of-use tariffs.

References:

[1] Fang K, Uhan N A, Zhao F, et al. Scheduling on a single machine under time-of-use electricity tariffs [J]. Annals of Operations Research, 2016, 238(1/2): 199-227. DOI:10.1007/s10479-015-2003-5.
[2] Seidgar H, Zandieh M, Mahdavi I. Bi-objective optimization for integrating production and preventive maintenance scheduling in two-stage assembly flow shop problem [J]. Journal of Industrial and Production Engineering, 2016, 33(6): 404-425. DOI:10.1080/21681015.2016.1173599.
[3] Wang S, Liu M. Two-machine flow shop scheduling integrated with preventive maintenance planning [J]. International Journal of Systems Science, 2016, 47(3): 672-690. DOI:10.1080/00207721.2014.900137.
[4] Das Adhikary D, Bose G K, Jana D K, et al. Availability and cost-centered preventive maintenance scheduling of continuous operating series systems using multi-objective genetic algorithm: A case study [J]. Quality Engineering, 2016, 28(3): 352-357. DOI:10.1080/08982112.2015.1086001.
[5] Nourelfath M, Fitouhi M C, Machani M. An integrated model for production and preventive maintenance planning in multi-state systems [J]. IEEE Transactions on Reliability, 2010, 59(3): 496-506. DOI:10.1109/tr.2010.2056412.
[6] Liu B Y, Chen W D. Single-machine scheduling with preventive periodic maintenance and resumable jobs in remanufacturing system [J]. Journal of Southeast University: English Edition, 2012, 28(3): 349-353.
[7] Yu X, Zhang Y, Xu D, et al. Single machine scheduling problem with two synergetic agents and piece-rate maintenance [J]. Applied Mathematical Modelling, 2013, 37(3): 1390-1399. DOI:10.1016/j.apm.2012.04.009.
[8] Xue P, Zhang Y, Yu X. Single-machine scheduling with piece-rate maintenance and interval constrained position-dependent processing times [J]. Applied Mathematics and Computation, 2014, 226: 415-422. DOI:10.1016/j.amc.2013.10.034.
[9] Shrouf F, Ordieres-Meré J, García-Sánchez A, et al. Optimizing the production scheduling of a single machine to minimize total energy consumption costs [J]. Journal of Cleaner Production, 2014, 67: 197-207. DOI:10.1016/j.jclepro.2013.12.024.
[10] Yildirim M B, Mouzon G. Single-machine sustainable production planning to minimize total energy consumption and total completion time using a multiple objective genetic algorithm [J]. IEEE Transactions on Engineering Management, 2012, 59(4): 585-597. DOI:10.1109/tem.2011.2171055.
[11] Tan Y, Huang Y, Liu S. Two-stage mathematical programming approach for steelmaking process scheduling under variable electricity price [J]. Journal of Iron and Steel Research, International, 2013, 20(7): 1-8. DOI:10.1016/s1006-706x(13)60118-1.
[12] Liu C H, Huang D H. Reduction of power consumption and carbon footprints by applying multi-objective optimisation via genetic algorithms [J]. International Journal of Production Research, 2014, 52(2): 337-352. DOI:10.1080/00207543.2013.825740.
[13] Ding J Y, Song S, Zhang R, et al. Parallel machine scheduling under time-of-use electricity prices: New models and optimization approaches [J]. IEEE Transactions on Automation Science and Engineering, 2016, 13(2): 1138-1154. DOI:10.1109/tase.2015.2495328.
[14] Che A, Zeng Y, Lyu K. An efficient greedy insertion heuristic for energy-conscious single machine scheduling problem under time-of-use electricity tariffs [J]. Journal of Cleaner Production, 2016, 129: 565-577. DOI:10.1016/j.jclepro.2016.03.150.
[15] Moon J Y, Shin K, Park J. Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency [J]. The International Journal of Advanced Manufacturing Technology, 2013, 68(1/2/3/4): 523-535. DOI: 10.1007/s00170-013-4749-8.
[16] Sharma A, Zhao F, Sutherland J W. Econological scheduling of a manufacturing enterprise operating under a time-of-use electricity tariff [J]. Journal of Cleaner Production, 2015, 108: 256-270. DOI: 10.1016/j.jclepro.2015.06.002.
[17] Tan Y Y, Liu S X. Models and optimisation approaches for scheduling steelmaking-refining-continuous casting production under variable electricity price [J]. International Journal of Production Research, 2014, 52(4): 1032-1049. DOI: 10.1080/00207543.2013.828179.
[18] McKay K, Pinedo M, Webster S. Practice-focused research issues for scheduling systems [J]. Production and Operations Management, 2002, 11(2): 249-258. DOI: 10.1111/j.1937-5956.2002.tb00494.x.

Memo

Memo:
Biographies: Wei Li(1984—), female, Ph.D.candidate;Chen Weida(corresponding author), male, doctor, professor, cwd@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.71271054, 71571042, 71501046), the Fundamental Research Funds for the Central Universities(No.2242015S32023), the Scientific Research Innovation Project for College Graduates in Jiangsu Province(No.CXZZ12_0133).
Citation: Wei Li, Chen Weida, Yang Ye. Scheduling optimization problem considering time-of-use tariffs and piece-rate machine maintenance in EAF steelmaking[J].Journal of Southeast University(English Edition), 2018, 34(1):127-134.DOI:10.3969/j.issn.1003-7985.2018.01.018.
Last Update: 2018-03-20