Flexible Job-Shop Scheduling Problem with Maintenance Activities Considering Energy Consumption

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With the developing of industry, the topic of energy-saving is attracting more and more attentions. However, the attentions have focused primarily on the design activities of the firm. The planning/scheduling activities of manufacturing are neglected. In this paper, a mathematical model, which considers the energy consumption and preventive maintenance of equipment in the flexible job shop, is established, three objectives, such as the minimization of maximum completion time, the minimization of total production energy costs and the minimization of total energy costs of maintenance that are quantized by electricity, are taken into account. The algorithm of NSGA-II is presented to solve the optimization model, and experimental results validate the effectiveness of the proposed approach.

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707-713

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February 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] EIA. International Energy Outlook 2011, Highlight, pp.1-8.

Google Scholar

[2] EIA. Annual Energy Outlook (2013).

Google Scholar

[3] GAO Jie, GEN M, et al. Scheduling jobs and maintenances in flexible job shop with a hybrid genetic algorithm[J]. Journal of Intelligent Manufacturing, 2006, 17(4): 493-507.

DOI: 10.1007/s10845-005-0021-x

Google Scholar

[4] WANG Shijin, YU Jianbo. An effective heuristic for flexible job-shop scheduling problem with maintenance activities[J]. Computers & Industrial Engineering, 2010, 59(3): 436-447.

DOI: 10.1016/j.cie.2010.05.016

Google Scholar

[5] MORADI E, FATEMI G S, et al. Bi-objective optimization research on integrated fixed time interval preventive maintenance and production for scheduling flexible job-shop problem[J]. Expert systems with applications, 2011, 38(6): 7169-7178.

DOI: 10.1016/j.eswa.2010.12.043

Google Scholar

[6] LI Junqing, PAN Quanke. Chemical-reaction optimization for flexible job-shop scheduling problems with maintenance activity[J]. Applied Soft Computing, 2012, 2(9): 2896-2912.

DOI: 10.1016/j.asoc.2012.04.012

Google Scholar

[7] Wang, L., G. Zhou, et al. An effective artificial bee colony algorithm for the flexible job-shop scheduling problem[J]. The International Journal of Advanced Manufacturing Technology. 2012, 60(1-4): 303-315.

DOI: 10.1007/s00170-011-3610-1

Google Scholar

[8] Crow L.H., Reliability analysis for Complex Repairable Systems. Reliability and Biometry, Philadelphia: SIAM, (1974).

Google Scholar

[9] Camposeco-Negrete, C. Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA[J]. Journal of Cleaner Production, 2013, 53, 195-203.

DOI: 10.1016/j.jclepro.2013.03.049

Google Scholar

[10] M. B. Yildirim. A framework to minimise total energy consumption and total tardiness on a single machine[J]. International Journal of Sustainable Engineering, 2008, 1(2): 105-116.

DOI: 10.1080/19397030802257236

Google Scholar

[11] Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. A fast and elitist multi objective genetic algorithm: NSGA-II[C]. Evolutionary Computation, IEEE Transactions on, 2002, 6(2), 182-197.

DOI: 10.1109/4235.996017

Google Scholar

[12] Kacem I, Hammadi S, Borne P. Pareto-optimality approach for flexible job-shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic[J]. Math ComputSimul, 2002, 60(3–5): 245–276.

DOI: 10.1016/s0378-4754(02)00019-8

Google Scholar