Open AccessA multi-objective optimization method based on NSGA-III for water quality sensor placement with the aim of reducing potential contamination of important nodes
Author(s) -
Hamideh Jafari,
Sara Nazif,
Taher Rajaee
Publication year - 2021
Publication title -
water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2021.222
Subject(s) - benchmark (surveying) , contamination , pareto optimal , computer science , pareto principle , mathematical optimization , multi objective optimization , volume (thermodynamics) , population , mathematics , ecology , physics , demography , geodesy , quantum mechanics , sociology , biology , geography
One way to mitigate the risk of consumption of contaminated water in water distribution networks is optimal placement of the quality sensors. A considerable challenge in this respect is the significance of contamination at a junction. Beside the population affected and the volume of the contaminated water consumed, importance of each junction is a parameter that must be taken into account in placing the sensors. This parameter directly concerns the service provided by each junction as well as the sensitivity and social consequences of junction contamination. The present study defines a new objective function for minimizing the effect of junction contamination with respect to its importance. Using a robust approach, this study applied the NSGA-III algorithm to solve a 5-objective problem. The algorithm was tested on a hypothetical network and a benchmark network and the Pareto response was selected for each scenario based on the slope of the different points. The proposed method suggested 12, 12, and 11 sensors for the three scenarios in the hypothetical network. The results show that sensor placement by this method yielded good performance in comparison with the other solutions presented in a benchmark network.