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}.
References
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)
Bohórques, J., Saldarriaga, J., Vallejo, D.: Pumping pattern optimization in order to reduce WDS operation costs. Procedia Eng. 119, 1069–1077 (2015)
Alrheeh, M., Mahmoud, H.: Using Genetics Algorithms in Pump Scheduling to Reduce the Pumping Cost. Damascous Univ. J. 25(2), 95–105 (2009)
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
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)
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
Mazurkiewicz, D., Rudawska, A. (eds.): Inspirations for Innovation: the Causes and Effects of Progress in Production Engineering. Monograph. Lublin University of Technology, Lublin (2016)
Jowitt, P.W., Germanopolous, G.: Optimal pump scheduling in water-supply networks. J. Water Resour. Plan. Manag. 118(4), 406–422 (1992)
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)
Lansey, K.E., Awumah, K.: Optimal pump operations considering pump switches. J. Water Resour. Plan. Manag. 120, 17–35 (1994)
Ormsbee, L.E., Reddy, S.L.: Nonlinear heuristic for pump operations. J. Water. Resour. Plan. Manag. 121(4), 302–309 (1995)
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)
Baran, B., Lücken, C., Sotelo, A.: Multi-objective pump scheduling optimisation using evolutionary strategies. Adv. Eng. Softw. 36, 39–47 (2005)
Puleo, V., Morley, M., Freni, G., Savić, D.: Multi-stage linear programming optimization for pump scheduling. Procedia Eng. 70, 1378–1385 (2014)
Walters, G.A., Savić, D.A.: Recent applications of genetic algorithms to water system design. Trans. Ecol. Environ. 12, 143–152 (1996). WIT Press
Borkowski, D., Wetula, A., Bień, A.: Design, optimization, and deployment of waterworks pumping station control system. ISA Trans. 51, 539–549 (2012)
Behandish, M., Wu, Z.Y.: Concurrent pump scheduling and storage level optimization using meta-models and evolutionary algorithms. Procedia Eng. 70, 103–112 (2014)
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)
Ormsbee, L.E., Lansey, K.E.: Optimal control of water supply pumping systems. J. Water Resour. Plan. Manag. ASCE 120(2), 237–252 (1994)
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)
Giacomello, C., Kapelan, Z., Nicolini, M.: Fast Hybrid optimization metod for effective pump scheduling. J. Water Resour. Plan. Manag. 139(2), 175–183 (2013)
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)
Kłos, S., Patalas-Maliszewska, J., Trebuna, P.: Improving manufacturing processes using simulation methods. Appl. Comput. Sci. 12(4), 42–53 (2016)
Loska, A.: Methodology of variant assessment of exploitation policy using numerical taxonomy tools. Manag. Syst. Prod. Eng. 2(18), 98–104 (2015)
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)
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
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights 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)