Skip to main content

Binary Linear Programming as a Decision-Making Aid for Water Intake Operators

  • Conference paper
  • First Online:
Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017 (ISPEM 2017)

Abstract

The cost of energy consumed in the course of pumping water from its sources constitutes a considerable share of the total operating costs borne by a water company. In order to optimize the operation of a water pumping station, it is essential to devise an appropriate pumps schedule. The aim of the work was to develop a smart tool which would facilitate decision-making by the operator of a water intake, including a group of wells, supplying actual municipal waterworks. The tool creates a real-time schedule for wells and pumps integrated with them, which constitutes a basis for a final decision made by the operator, related to the degree and period of their usage. The main criterion of facilitating the decision-making pertained to achieving the minimum energy consumption during pumping water from a well to a reservoir tank, while simultaneously keeping all the wells on full stand-by. The schedule was prepared by means of binary linear programming. In this method, both the function of the goal and the limiting functions are linear, whereas the particular variables belong to the set {0,1}.

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

Access this chapter

Institutional subscriptions

References

  1. Abkenar, S.M.S., Stanley, S.D., Miller, C.J., Chase, D.V., McElmurry, S.P.: Evaluation of genetic algorithms using discrete and continuous method for pump optimization of water distribution system. Sustain. Comput: Inform. Syst. 8, 18–23 (2015)

    Article  Google Scholar 

  2. Bohórques, J., Saldarriaga, J., Vallejo, D.: Pumping pattern optimization in order to reduce WDS operation costs. Procedia Eng. 119, 1069–1077 (2015)

    Article  Google Scholar 

  3. Alrheeh, M., Mahmoud, H.: Using Genetics Algorithms in Pump Scheduling to Reduce the Pumping Cost. Damascous Univ. J. 25(2), 95–105 (2009)

    Google Scholar 

  4. Kosicka, E., Kozłowski, E., Mazurkiewicz, D.: The use of stationary tests for analysis of monitored residual processes. Eksploatacja i Niezawodność – Maint. Reliab. 17(4), 604–609 (2015). doi:10.17531/ein.2015.4.17

    Article  Google Scholar 

  5. Rojek, I., Studziński, J.: Comparison of different types of neuronal nets for failures location within water-supply networks. Eksploatacja i Niezawodność – Maint. Reliab. 16(1), 42–47 (2014)

    Google Scholar 

  6. Romaniuk, M.: On simulation of maintenance costs for water distribution system with fuzzy parameters. Eksploatacja i Niezawodnosc – Maint. Reliab. 18(4), 514–527 (2016). doi:10.17531/ein.2016.4.6

    Article  Google Scholar 

  7. Mazurkiewicz, D., Rudawska, A. (eds.): Inspirations for Innovation: the Causes and Effects of Progress in Production Engineering. Monograph. Lublin University of Technology, Lublin (2016)

    Google Scholar 

  8. Jowitt, P.W., Germanopolous, G.: Optimal pump scheduling in water-supply networks. J. Water Resour. Plan. Manag. 118(4), 406–422 (1992)

    Article  Google Scholar 

  9. Yu, G., Powell, R.S., Sterling, M.J.H.: Optimized pump scheduling un water distribution system. J. Optim. Theory Appl. 83(3), 463–488 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  10. Lansey, K.E., Awumah, K.: Optimal pump operations considering pump switches. J. Water Resour. Plan. Manag. 120, 17–35 (1994)

    Article  Google Scholar 

  11. Ormsbee, L.E., Reddy, S.L.: Nonlinear heuristic for pump operations. J. Water. Resour. Plan. Manag. 121(4), 302–309 (1995)

    Article  Google Scholar 

  12. Wang, Y.A., Chang, T.P., Chen, J.S.: An enhanced genetic algorithm for bi-objective pump scheduling in water supply. Expert Syst. Appl. 36, 10249–10258 (2009)

    Article  Google Scholar 

  13. Baran, B., Lücken, C., Sotelo, A.: Multi-objective pump scheduling optimisation using evolutionary strategies. Adv. Eng. Softw. 36, 39–47 (2005)

    Article  MATH  Google Scholar 

  14. Puleo, V., Morley, M., Freni, G., Savić, D.: Multi-stage linear programming optimization for pump scheduling. Procedia Eng. 70, 1378–1385 (2014)

    Article  Google Scholar 

  15. Walters, G.A., Savić, D.A.: Recent applications of genetic algorithms to water system design. Trans. Ecol. Environ. 12, 143–152 (1996). WIT Press

    Google Scholar 

  16. Borkowski, D., Wetula, A., Bień, A.: Design, optimization, and deployment of waterworks pumping station control system. ISA Trans. 51, 539–549 (2012)

    Article  Google Scholar 

  17. Behandish, M., Wu, Z.Y.: Concurrent pump scheduling and storage level optimization using meta-models and evolutionary algorithms. Procedia Eng. 70, 103–112 (2014)

    Article  Google Scholar 

  18. Savić, D.A., Walters, G.A., Schwab, M.: Multiobjective genetic algorithms for pump scheduling in water supply, in Evolutionary Computing Lecture Notes in Computer Science, Springer. 1305, 227–235 (1997)

    Google Scholar 

  19. Ormsbee, L.E., Lansey, K.E.: Optimal control of water supply pumping systems. J. Water Resour. Plan. Manag. ASCE 120(2), 237–252 (1994)

    Article  Google Scholar 

  20. Pasha, M.F.K., Lansey, K.: Optimal pump scheduling by linear programming. In: Proceedings of World Environmental and Water Resources Congress, Kansas City, Missouri, pp. 395–404 (2009)

    Google Scholar 

  21. Giacomello, C., Kapelan, Z., Nicolini, M.: Fast Hybrid optimization metod for effective pump scheduling. J. Water Resour. Plan. Manag. 139(2), 175–183 (2013)

    Article  Google Scholar 

  22. Jasiulewicz-Kaczmarek, M.: Practical aspects of the application of RCM to select optimal maintenance policy of the production line. In: Nowakowski, T., Mlynczak, M., Jodejko-Pietruczuk, A., et al. (eds.) Safety and Reliability: Methodology and Applications - Proceedings of the European Safety and Reliability Conference, ESREL 2014, Wroclaw, Poland, Sep 14–18, 2014, Taylor & Francis Group, London, pp. 1187–1195 (2015)

    Google Scholar 

  23. Kłos, S., Patalas-Maliszewska, J., Trebuna, P.: Improving manufacturing processes using simulation methods. Appl. Comput. Sci. 12(4), 42–53 (2016)

    Google Scholar 

  24. Loska, A.: Methodology of variant assessment of exploitation policy using numerical taxonomy tools. Manag. Syst. Prod. Eng. 2(18), 98–104 (2015)

    Google Scholar 

  25. Valis, D., Pietrucha-Urbanik, K.: Utilization of diffusion processes and fuzzy logic for vulnerability assessment. Eksploatacja i Niezawodnosc – Maint. Reliab. 16(1), 48–55 (2014)

    Google Scholar 

  26. Ostapkowicz, P., Bratek, A.: Possible leakage detection level in transmission pipelines using improved simplified methods. Eksploatacja i Niezawodnosc – Maint. Reliab. 18(3), 469–480 (2016). doi:10.17531/ein.2016.3.20

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Edward Kozłowski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Kozłowski, E., Mazurkiewicz, D., Kowalska, B., Kowalski, D. (2018). Binary Linear Programming as a Decision-Making Aid for Water Intake Operators. In: Burduk, A., Mazurkiewicz, D. (eds) Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017. ISPEM 2017. Advances in Intelligent Systems and Computing, vol 637. Springer, Cham. https://doi.org/10.1007/978-3-319-64465-3_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64465-3_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64464-6

  • Online ISBN: 978-3-319-64465-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics