Skip to main content Accessibility help
×
×
Home

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

  • Miguel A. Salido (a1), Joan Escamilla (a1), Federico Barber (a1), Adriana Giret (a1), Dunbing Tang (a2) and Min Dai (a2)...

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.

Copyright

Corresponding author

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

References

Hide All
Agnetis, A., Flamini, M., Nicosia, G., & Pacifici, A. (2011). A job-shop problem with one additional resource type. Journal of Scheduling 14(3), 225237.
Billaut, J.C., Moukrim, A., & Sanlaville, E. (2008). Flexibility and Robustness in Scheduling. Hoboken, NJ: Wiley.
Blazewicz, J., Cellary, W., Slowinski, R., & Weglarz, J. (1986). Scheduling under resource constraints-deterministic models. Annals of Operations Research 7, 1356.
BMWi. (2009). German Federal Ministry of Economics and Technology: Energy Statistics. Berlin: Author.
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), 459462.
Caplinskas, A., Dzemyda, G., Kiss, F., & Lupeikiene, A. (2012). Processing of undesirable business events in advanced production planning systems. Informatica: International Journal 23(4), 563579.
Dahmus, J., & Gutowski, T. (2004). An environmental analysis of machining. Proc. ASME Int. Mechanical Engineering Congr. RD&D Exposition, Anaheim, CA.
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), 418429.
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), 587609.
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), 234240.
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.
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), 117.
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), 10301046.
IBM. (2010). Modeling With IBM ILOG CP Optimizer—Practical Scheduling Examples (white paper). Armonk, NY: IBM Software Group.
Kramer, L., Barbulescu, L., & Smith, S. (2007). Understanding performance tradeoffs in algorithms for solving oversubscribed scheduling. Proc. 22nd Conf. Artificial Intelligence, AAAI-07, Vancouver.
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.
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. 268273. Berlin: Springer.
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), 105116.
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), 42474271.
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), 136147.
Nowicki, E., & Smutnicki, C. (2005). An advanced tabu search algorithm for the job shop problem. Journal of Scheduling 8(2), 145159.
Seow, Y., & Rahimifard, S. (2011). A framework for modelling energy consumption within manufacturing systems. CIRP Journal of Manufacturing Science and Technology 4(3), 258264.
Szathmary, E. (2006). A robust approach. Nature 439, 1920.
Verfaillie, G., & Schiex, T. (1994). Solution reuse in dynamic constraint satisfaction problems. Proc. 12th National Conf. Artificial Intelligence, AAAI-94.
Weinert, N., Chiotellis, S., & Seliger, G. (2011). Methodology for planning and operating energy-efficient production systems. CIRP Annals-Manufacturing Technology 60(1), 4144.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

AI EDAM
  • ISSN: 0890-0604
  • EISSN: 1469-1760
  • URL: /core/journals/ai-edam
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed