Multi-objective branch-and-bound for the design-for-control of water distribution networks with global bounds

Published: 1 February 2023| Version 1 | DOI: 10.17632/chsxc89s8r.1
Joy Ulusoy


This dataset describes the multi-objective design-for-control problems and presents the obtained results for two network models (modified Net25 and pescara) studied in the publication "Multi-objective branch-and-bound for the design-for-control of water distribution networks with global bounds", by Aly-Joy Ulusoy and Ivan Stoivanov. The general design-for-control problem consists in simultaneously selecting elements to be added to the existing water distribution networks (WDN) from predefined sets of candidate valves (CNV) and pipes (CNP), and optimizing the controls of new and existing pressure control valves. The problem considers the conflicting objectives of AZP (or average zone pressure, a surrogate measure of pressure induced pipe stress and leakage), I_r (or resilience index, a surrogate measure of network resilience) and cost. We refer to the main manuscript for a definition of the objective functions, problem formulation and discussion of the results of the multi-objective design-for-control problems. The information and results provided in this dataset aim to facilitate future comparison of our work against alternative solution methods. Accordingly, we provide below, for each network model: - the .inp network model, to access using EPANET or a text editor, with characteristics of network pipes (diameter, length, roughness coefficients) and nodes (elevation, demand). Please use the provided network models (25nodes_PRVs2.inp and pescara_ed.inp) for comparison purposes, as the original models they are based on have been modified for the purpose of this study. - a description of the design-for-control problem investigated by the authors of the main manuscript and corresponding to the presented results Finally, we refer the reader to the main manuscript for illustrations and discussions of the results.



Imperial College London


Global Optimization, Multi-Objective Optimization, Water Distribution