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Energy efficiency, robustness, and makespan optimality in job-shop scheduling problems

Published online by Cambridge University Press:  09 June 2015

Miguel A. Salido ,
Joan Escamilla ,
Federico Barber ,
Adriana Giret ,
Dunbing Tang  and
Min Dai
Miguel A. Salido*
Affiliation:
Instituto de Automática e Informática Industrial, Universitat Politecnica de Valencia, Spain
Joan Escamilla
Affiliation:
Instituto de Automática e Informática Industrial, Universitat Politecnica de Valencia, Spain
Federico Barber
Affiliation:
Instituto de Automática e Informática Industrial, Universitat Politecnica de Valencia, Spain
Adriana Giret
Affiliation:
Instituto de Automática e Informática Industrial, Universitat Politecnica de Valencia, Spain
Dunbing Tang
Affiliation:
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, China
Min Dai
Affiliation:
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, China
*
Reprint requests to: Miguel A. Salido, Instituto de Automática e Informática Industrial, Universitat Politecnica de Valencia, Camino de Vera s/n, Valencia 46071, Spain. E-mail: msalido@dsic.upv.es
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Abstract

Many real-world problems are known as planning and scheduling problems, where resources must be allocated so as to optimize overall performance objectives. The traditional scheduling models consider performance indicators such as processing time, cost, and quality as optimization objectives. However, most of them do not take into account energy consumption and robustness. We focus our attention in a job-shop scheduling problem where machines can work at different speeds. It represents an extension of the classical job-shop scheduling problem, where each operation has to be executed by one machine and this machine can work at different speeds. The main goal of the paper is focused on the analysis of three important objectives (energy efficiency, robustness, and makespan) and the relationship among them. We present some analytical formulas to estimate the ratio/relationship between these parameters. It can be observed that there exists a clear relationship between robustness and energy efficiency and a clear trade-off between robustness/energy efficiency and makespan. It represents an advance in the state of the art of production scheduling, so obtaining energy-efficient solutions also supposes obtaining robust solutions, and vice versa.

Keywords

Energy EfficiencyJob-Shop SchedulingParameter RelationshipRobustness

Information

Type
Regular Articles
Information
AI EDAM , Volume 30 , Special Issue 3: System Architecture Design , August 2016 , pp. 300 - 312
Copyright
Copyright © Cambridge University Press 2015 

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References

REFERENCES

Agnetis, A., Flamini, M., Nicosia, G., & Pacifici, A. (2011). A job-shop problem with one additional resource type. Journal of Scheduling 14(3), 225–237.Google Scholar
Billaut, J.C., Moukrim, A., & Sanlaville, E. (2008). Flexibility and Robustness in Scheduling. Hoboken, NJ: Wiley.CrossRefGoogle Scholar
Blazewicz, J., Cellary, W., Slowinski, R., & Weglarz, J. (1986). Scheduling under resource constraints-deterministic models. Annals of Operations Research 7, 1–356.Google Scholar
BMWi. (2009). German Federal Ministry of Economics and Technology: Energy Statistics. Berlin: Author.Google Scholar
Bruzzone, A.A.G., Anghinolfi, D., Paolucci, M., & Tonelli, F. (2012). Energy-aware scheduling for improving manufacturing process sustainability: a mathematical model for flexible flow shops. CIRP Annals-Manufacturing Technology 61(1), 459–462.Google Scholar
Caplinskas, A., Dzemyda, G., Kiss, F., & Lupeikiene, A. (2012). Processing of undesirable business events in advanced production planning systems. Informatica: International Journal 23(4), 563–579.CrossRefGoogle Scholar
Dahmus, J., & Gutowski, T. (2004). An environmental analysis of machining. Proc. ASME Int. Mechanical Engineering Congr. RD&D Exposition, Anaheim, CA.CrossRefGoogle Scholar
Dai, M., Tang, D., Giret, A., Salido, M.A., & Li, W.D. (2013). Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm. Robotics and Computer-Integrated Manufacturing 29(5), 418–429.Google Scholar
Duflou, J.R., Sutherland, J.W., Dornfeld, D., Herrmann, C., Jeswiet, J., Kara, S., Hauschild, M., & Kellens, K. (2012). Towards energy and resource efficient manufacturing: a processes and systems approach. CIRP Annals-Manufacturing Technology 61(2), 587–609.Google Scholar
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(4), 234–240.CrossRefGoogle Scholar
Garrido, A., Salido, M.A., Barber, F., & López, M.A. (2000). Heuristic methods for solving job-shop scheduling problems. Proc. ECAI-2000 Workshop on New Results in Planning, Scheduling and Design, Berlín.Google Scholar
Gutowski, T., Murphy, C., Allen, D., Bauer, D., Bras, B., Piwonka, T., Sheng, P., Sutherland, J., Thurston, D., & Wolff, E. (2005). Environmentally benign manufacturing: observations from Japan, Europe and the United States. Journal of Cleaner Production 13(1), 1–17.Google Scholar
Huang, K.L., & Liao, C.J. (2008). Ant colony optimization combined with taboo search for the job shop scheduling problem. Computers & Operations Research 35(4), 1030–1046.Google Scholar
IBM. (2010). Modeling With IBM ILOG CP Optimizer—Practical Scheduling Examples (white paper). Armonk, NY: IBM Software Group.Google Scholar
Kramer, L., Barbulescu, L., & Smith, S. (2007). Understanding performance tradeoffs in algorithms for solving oversubscribed scheduling. Proc. 22nd Conf. Artificial Intelligence, AAAI-07, Vancouver.Google Scholar
Laborie, P. (2009). IBM ILOG CP Optimizer for detailed scheduling illustrated on three problems. Proc. 6th Int. Conf. Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR09.Google Scholar
Li, W., Zein, A., Kara, S., & Herrmann, C. (2011). An investigation into fixed energy consumption of machine tools. In Glocalized Solutions for Sustainability in Manufacturing, pp. 268–273. Berlin: Springer.Google Scholar
Mouzon, G., & Yildirim, M.B. (2008). A framework to minimise total energy consumption and total tardiness on a single machine. International Journal of Sustainable Engineering 1(2), 105–116.CrossRefGoogle Scholar
Mouzon, G., Yildirim, M.B., & Twomey, J. (2007). Operational methods for minimization of energy consumption of manufacturing equipment. International Journal of Production Research 45(18–19), 4247–4271.Google Scholar
Neugebauer, R., Wabner, M., Rentzsch, H., & Ihlenfeldt, S. (2011). Structure principles of energy efficient machine tools. CIRP Journal of Manufacturing Science and Technology 4(2), 136–147.Google Scholar
Nowicki, E., & Smutnicki, C. (2005). An advanced tabu search algorithm for the job shop problem. Journal of Scheduling 8(2), 145–159.Google Scholar
Seow, Y., & Rahimifard, S. (2011). A framework for modelling energy consumption within manufacturing systems. CIRP Journal of Manufacturing Science and Technology 4(3), 258–264.CrossRefGoogle Scholar
Szathmary, E. (2006). A robust approach. Nature 439, 19–20.Google Scholar
Verfaillie, G., & Schiex, T. (1994). Solution reuse in dynamic constraint satisfaction problems. Proc. 12th National Conf. Artificial Intelligence, AAAI-94.Google Scholar
Weinert, N., Chiotellis, S., & Seliger, G. (2011). Methodology for planning and operating energy-efficient production systems. CIRP Annals-Manufacturing Technology 60(1), 41–44.Google Scholar