Skip to main content

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 524))

Abstract

Two immune algorithms were selected in the process of searching for an algorithm which achieves a good quality basic schedule, i.e. Multi Objective Immune Algorithm (MOIA), Clonal Selection Algorithm (CSA). The two algorithms are applied for a multi criteria job shop scheduling problem. The basic schedules are modified using the rule of the Minimal Impact of Disturbed Operation on the Schedule (MIDOS) in order to generate predictive schedules. The influence of rescheduling policies over the performance of the job shop system is investigated using the rule of the Minimal Impact of Rescheduled Operation on the Schedule (MIROS). The three steps are proposed in order to achieve robust and stable schedules. In this paper the algorithms are presented. In the second paper (under the title of On the Quality of Basic Schedules Influencing over the Performance of Predictive and Reactive Schedules), the influence of the quality of basic schedules on the obtainment of stable and robust schedules with the application of the MIDOS and MIROS is investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Paprocka, I., Kempa, W.M., Kalinowski, K., Grabowik, C.: Estimation of overall equipment effectiveness using simulation programme. Mater. Sci. Eng. 95, Article Number: 012155, 1–6 (2015)

    Google Scholar 

  2. Guilherme, E.V., Herrmann, J.W., Lin, E.: Rescheduling manufacturing systems: a framework of strategies, policies, and methods. J. Sched. 6(1), 35–58 (2003)

    MathSciNet  MATH  Google Scholar 

  3. Fahmy, S.A., Balakrishnan, S., ElMekkawy, T.Y.: A generic deadlock-free reactive scheduling approach. Int. J. Prod. Res. 47(20), 5657–5676 (2009)

    Article  MATH  Google Scholar 

  4. Hamzadayi, A., Yildiz, G.: Event driven strategy based complete rescheduling approaches for dynamic m identical parallel machines scheduling problem with a common server. Comput. Ind. Eng. 91, 66–84 (2016)

    Article  Google Scholar 

  5. Liu, L., Han-yu, G., Yu-geng, X.: Robust and stable scheduling of a single machine with random machine breakdowns. Int. J. Adv. Manuf. Technol. 31, 645–656 (2007)

    Article  Google Scholar 

  6. Kis, T., Pesch, E.: A review of exact solution methods for the non-preemptive multiprocessor flowshop problem. Eur. J. Oper. Res. 164, 592–608 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  7. Huo, J., Leung, Y.-T., Zhao, H.: Bi-criterial scheduling problems. Number of tardy jobs and maximum weighted tardiness. Eur. J. Oper. Res. 177, 116–134 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  8. Cheng, R., Gen, M., Tsujimura, Y.: A tutorial survey of job-shop scheduling problems using genetic algorithms, Part II: hybrid genetic search strategies. Comput. Ind. Eng. 36, 343–346 (1999)

    Article  Google Scholar 

  9. Mattfeld, D.C., Bierwirth, Ch.: An efficient genetic algorithm for job shop scheduling with tardiness objectives. Eur. J. Oper. Res. 155, 616–630 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  10. Liao, G-Ch.: Short-term thermal generation scheduling using improved immune algorithm. Electr. Power Syst. Res. 76, 360–375 (2006)

    Article  Google Scholar 

  11. de Castro, L.N., von Zuben, F.J.: Artificial immune systems: Part I—basic theory and applications. Technical Report. TR-DCA 01/99 (1999)

    Google Scholar 

  12. Tsai, J.-T., Ho, W.-H.: Improved immune algorithm for global numerical optimization and job-shop scheduling problems. Appl. Math. Comput. 194, 406–424 (2007)

    MathSciNet  MATH  Google Scholar 

  13. Ponnambalam, S.G., Jagannathan, H., Kataria, M., Gadicherla, A.: A TSP-GA multi-objective algorithm for flow-shop scheduling. Int. J. Adv. Manuf. Technol. 23, 909–915 (2004)

    Article  Google Scholar 

  14. Liaw, Ch-F: A hybrid genetic algorithm for the open shop scheduling problem. Eur. J. Oper. Res. 124, 28–42 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  15. Skołud, B., Wosik, I.: The development of IA with local search approach for multi-objective Job shop scheduling problem. In: 3rd International Conference Virtual Design and Automation, Poznań (2008)

    Google Scholar 

  16. Skołud, B., Wosik, I.: Multi-objective genetic and immune algorithms for batch scheduling problem with dependent setups. In: Recent Developments in Artificial Intelligence Methods, AIMETH. Gliwice, pp. 185–196 (2007)

    Google Scholar 

  17. Wosik, I.: An immune algorithm for scheduling and inspection of heuristics using into an initialization step. In: Information Systems Architecture and Technology. Decision Making Models, pp. 121–128 (2007)

    Google Scholar 

  18. Wosik, I.: A multi-objective immune algorithm and its application to the job shop scheduling. In: 10th International Symposium of Students and Young Mechanical Engineers. Advances in Mechanical Engineering, pp. 211–220. Gdańsk-Gdynia (2007)

    Google Scholar 

  19. Wierzchon, S.T.: Artificial immune systems. In: Theory and Application, Warsaw (2001) (in Polish)

    Google Scholar 

  20. Paprocka, I., Kempa, W.M., Grabowik, C., Kalinowski, K.: Predictive and reactive scheduling for a critical machine of a production system. Adv. Mater. Res. 1036, 909–914 (2014)

    Article  Google Scholar 

  21. Paprocka, I., Skołud, B.: Robust scheduling, a production scheduling model of failures. Appl. Mech. Mater. 307, 443–446 (2013)

    Article  Google Scholar 

  22. Ponnambalam, S.G., Ramkumar, V., Jawahar, N.: A multiobjective genetic algorithm for job shop scheduling. Prod. Plann. Control. 12(8), 764–774 (2001)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iwona Paprocka .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Paprocka, I., Kempa, W.M. (2017). Searching for a Method of Basic Schedules Generation Which Influences Over the Performance of Predictive and Reactive Schedules. In: Wilimowska, Z., Borzemski, L., Grzech, A., Świątek, J. (eds) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part IV. Advances in Intelligent Systems and Computing, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-319-46592-0_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-46592-0_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46591-3

  • Online ISBN: 978-3-319-46592-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics