scholarly journals A flexible methodology to sectorize water supply networks based on social network theory concepts and multi-objective optimization

2015 ◽  
Vol 18 (1) ◽  
pp. 62-76 ◽  
Author(s):  
Enrique Campbell ◽  
Joaquín Izquierdo ◽  
Idel Montalvo ◽  
Amilkar Ilaya-Ayza ◽  
Rafael Pérez-García ◽  
...  
Keyword(s):  
Social Network ◽  
Water Supply ◽  
Community Detection ◽  
Network Theory ◽  
Detection Algorithm ◽  
Social Network Theory ◽  
Multi Objective Optimization ◽  
Supply Networks ◽  
Multi Objective ◽  
Water Supply Networks

A novel methodology to sectorize water supply networks (WSNs) depending on a main transmission line is presented in this paper. The methodology is based on concepts derived from the social network theory and graph theory (namely, community detection and shortest path respectively); and also on a multi-objective optimization process by means of agent swarm optimization (ASO). A series of energy, operative, and economic criteria are optimized in this process. The core idea is to form sectors over the distribution network based on communities found using a community detection algorithm (Walktrap). The methodology is flexible and enables the technical staff in water utilities to make decisions at different stages. It has been tested by generating four feasible solutions over a portion of a real WSN.

scholarly journals Parallel Conical Area Community Detection Using Evolutionary Multi-Objective Optimization

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 111 ◽  
Author(s):  
Weiqin Ying ◽  
Hassan Jalil ◽  
Bingshen Wu ◽  
Yu Wu ◽  
Zhenyu Ying ◽  
...  
Keyword(s):  
Community Detection ◽  
Migration Policy ◽  
Detection Algorithm ◽  
Island Model ◽  
Multi Objective Optimization ◽  
Community Structures ◽  
Multi Objective ◽  
Local Search Strategy ◽  
Community Detection Algorithm ◽  
Global Selection

Detecting community structures helps to reveal the functional units of complex networks. In this paper, the community detection problem is regarded as a modularity-based multi-objective optimization problem (MOP), and a parallel conical area community detection algorithm (PCACD) is designed to solve this MOP effectively and efficiently. In consideration of the global properties of the selection and update mechanisms, PCACD employs a global island model and targeted elitist migration policy in a conical area evolutionary algorithm (CAEA) to discover community structures at different resolutions in parallel. Although each island is assigned only a portion of all sub-problems in the island model, it preserves a complete population to accomplish the global selection and update. Meanwhile the migration policy directly migrates each elitist individual to an appropriate island in charge of the sub-problem associated with this individual to share essential evolutionary achievements. In addition, a modularity-based greedy local search strategy is also applied to accelerate the convergence rate. Comparative experimental results on six real-world networks reveal that PCACD is capable of discovering potential high-quality community structures at diverse resolutions with satisfactory running efficiencies.

An Advanced Software to Manage a Smart Water Network with Innovative Metrics and Tools Based on Social Network Theory

10.29007/gvnz ◽  
2018 ◽  
Author(s):  
Armando Di Nardo ◽  
Michele Di Natale ◽  
Anna Di Mauro ◽  
Eva Martínez Díaz ◽  
Jose Antonio Blázquez Garcia ◽  
...  
Keyword(s):  
Social Network ◽  
Network Theory ◽  
Water Distribution ◽  
Distribution Networks ◽  
Social Network Theory ◽  
Geographical Information ◽  
Water Network ◽  
Time Data ◽  
Water Losses ◽  
Operational Conditions

The recent development and applications of social network theory in many fields of engineering (electricity, gas, transport, water, etc.) allows both the understanding of networks and to improve their management. Social network theory coupled to the availability of real time data and big data analysis techniques can change drastically the traditional approaches to manage civil networks. Recently, some authors are working to apply this novel approach, based on social network theory, on the water distribution networks using: a) graph partitioning algorithms to define optimal district meter areas both for water losses identification and for water network protection, b) innovative topological, energy and hydraulic indices to analyze performance; and c) GIS (Geographical Information System) to provide a more effective display of results and to improve network behavior in specific operational conditions. In this paper, a novel release 3.5 of SWANP software, that implements all these features, was tested on a real large water network in Alcalá de Henares, Spain.

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