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Mathematical programming techniques in water network optimization

Author

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  • D’Ambrosio, Claudia
  • Lodi, Andrea
  • Wiese, Sven
  • Bragalli, Cristiana

Abstract

In this article we survey mathematical programming approaches to problems in the field of drinking water distribution network optimization. Among the predominant topics treated in the literature, we focus on two different, but related problem classes. One can be described by the notion of network design, while the other is more aptly termed by network operation. The basic underlying model in both cases is a nonlinear network flow model, and we give an overview on the more specific modeling aspects in each case. The overall mathematical model is a Mixed Integer Nonlinear Program having a common structure with respect to how water dynamics in pipes are described. Finally, we survey the algorithmic approaches to solve the proposed problems and we discuss computation on various types of water networks.

Suggested Citation

  • D’Ambrosio, Claudia & Lodi, Andrea & Wiese, Sven & Bragalli, Cristiana, 2015. "Mathematical programming techniques in water network optimization," European Journal of Operational Research, Elsevier, vol. 243(3), pages 774-788.
    • Handle: RePEc:eee:ejores:v:243:y:2015:i:3:p:774-788
    DOI: 10.1016/j.ejor.2014.12.039
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    References listed on IDEAS

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    1. Ghaddar, Bissan & Naoum-Sawaya, Joe & Kishimoto, Akihiro & Taheri, Nicole & Eck, Bradley, 2015. "A Lagrangian decomposition approach for the pump scheduling problem in water networks," European Journal of Operational Research, Elsevier, vol. 241(2), pages 490-501.
    2. da Conceicao Cunha, Maria & Ribeiro, Luisa, 2004. "Tabu search algorithms for water network optimization," European Journal of Operational Research, Elsevier, vol. 157(3), pages 746-758, September.
    3. Rovatti, Riccardo & D’Ambrosio, Claudia & Lodi, Andrea & Martello, Silvano, 2014. "Optimistic MILP modeling of non-linear optimization problems," European Journal of Operational Research, Elsevier, vol. 239(1), pages 32-45.
    4. Björn Geißler & Oliver Kolb & Jens Lang & Günter Leugering & Alexander Martin & Antonio Morsi, 2011. "Mixed integer linear models for the optimization of dynamical transport networks," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 73(3), pages 339-362, June.
    5. Coelho, B. & Andrade-Campos, A., 2014. "Efficiency achievement in water supply systems—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 59-84.
    6. M. Collins & L. Cooper & R. Helgason & J. Kennington & L. LeBlanc, 1978. "Solving the Pipe Network Analysis Problem Using Optimization Techniques," Management Science, INFORMS, vol. 24(7), pages 747-760, March.
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