scholarly journals Hybrid metaheuristics for multi-objective design of water distribution systems

2013 ◽  
Vol 16 (1) ◽  
pp. 165-177 ◽  
Author(s):  
Qi Wang ◽  
Dragan A. Savić ◽  
Zoran Kapelan
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Hybrid Algorithms ◽  
Medium Size ◽  
Hybrid Metaheuristics ◽  
Nsga Ii ◽  
Multi Objective ◽  
Adaptive Capabilities ◽  
Wide Range

Multi-objective design of Water Distribution Systems (WDSs) has received considerable attention in the past. Multi-objective evolutionary algorithms (MOEAs) are popular in tackling this problem due to their ability to approach the true Pareto-optimal front (PF) in a single run. Recently, several hybrid metaheuristics based on MOEAs have been proposed and validated on test problems. Among these algorithms, AMALGAM and MOHO are two noteworthy representatives which mix their constituent algorithms in contrasting fashion. In this paper, they are employed to solve a wide range of benchmark design problems against another state-of-the-art algorithm, namely NSGA-II. The design task is formulated as a bi-objective optimisation problem taking cost and network resilience into account. The performance of three algorithms is assessed via normalised hypervolume indicator. The results demonstrate that AMALGAM is superior to MOHO and NSGA-II in terms of convergence and diversity on the networks of small-to-medium size; however, for larger networks, the performance of hybrid algorithms deteriorates as they lose their adaptive capabilities. Future improvement and/or redesign on hybrid algorithms should not only adopt the strategies of adaptive portfolios of sub-algorithms and global information sharing, but also prevent the deterioration mainly caused by imbalance of constituent algorithms.

scholarly journals Probabilistic building block identification for the optimal design and rehabilitation of water distribution systems

2009 ◽  
Vol 11 (2) ◽  
pp. 89-105 ◽  
Author(s):  
Ralph J. Olsson ◽  
Zoran Kapelan ◽  
Dragan A. Savic
Keyword(s):  
Genetic Algorithms ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Building Blocks ◽  
Probabilistic Methods ◽  
Chi Square ◽  
Nsga Ii ◽  
Multi Objective ◽  
The Cost

The multi-objective design and rehabilitation of water distribution systems (WDS) is defined as the search for the set of system designs which offers the best trade-off between competing design objectives. Typically these objectives will consist of the cost of implementing a system design and a measure of the performance of that system. These measures are often in competition since improvements in the performance of a system generally come at a cost. Here three genetic algorithms which use probabilistic methods to identify building blocks—the Univariate Marginal Distribution Algorithm (UMDA) (Mühlenbein 1997), the hierarchical Bayesian Optimisation Algorithm (hBOA) (Pelikan 2002) and the Chi-Square Matrix methodology (Aporntewan & Chongstitvatana 2004)—are compared to the well-known multi-objective evolutionary algorithm NSGAII (Deb et al. 2002) for the multi-objective design and rehabilitation of water distribution systems. For single-objective problems the identification of building blocks has been seen to make evolutionary algorithms more scalable to large problems than simple genetic algorithms. In this paper these algorithms are shown to offer significantly better solutions than NSGA-II for the case of large systems. However, this improvement comes at the expense of diversity of solutions in the fronts identified.

scholarly journals An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1334
Author(s):  
Mohamed R. Torkomany ◽  
Hassan Shokry Hassan ◽  
Amin Shoukry ◽  
Ahmed M. Abdelrazek ◽  
Mohamed Elkholy
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Large Network ◽  
Swarm Optimization ◽  
Original Algorithm ◽  
Multi Objective

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit of the currently available resources. One of these strategies is ensuring that reliable and near-optimum designs of water distribution systems (WDSs) are achieved. Designing WDSs is a discrete combinatorial NP-hard optimization problem, and its complexity increases when more objectives are added. Among the many existing evolutionary algorithms, a new hybrid fast-convergent multi-objective particle swarm optimization (MOPSO) algorithm is developed to increase the convergence and diversity rates of the resulted non-dominated solutions in terms of network capital cost and reliability using a minimized computational budget. Several strategies are introduced to the developed algorithm, which are self-adaptive PSO parameters, regeneration-on-collision, adaptive population size, and using hypervolume quality for selecting repository members. A local search method is also coupled to both the original MOPSO algorithm and the newly developed one. Both algorithms are applied to medium and large benchmark problems. The results of the new algorithm coupled with the local search are superior to that of the original algorithm in terms of different performance metrics in the medium-sized network. In contrast, the new algorithm without the local search performed better in the large network.

Robust booster chlorination in water distribution systems: design and operational perspectives under uncertainty

2019 ◽  
Vol 68 (6) ◽  
pp. 399-410
Author(s):  
Denis Nono ◽  
Innocent Basupi
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Systems Design ◽  
Nsga Ii ◽  
Chlorine Disinfection ◽  
Uncertain Network ◽  
Network Operations ◽  
Booster Chlorination ◽  
Injection Rates

Abstract Booster chlorination designs have been widely based on predefined (deterministic) network conditions and they perform poorly under uncertainty in water distribution systems (WDSs). This paper presents a scenario-based robust optimisation approach which was developed to obtain booster chlorination designs that withstand uncertain network operations and water demand conditions in the WDSs. An optimisation problem was formulated to minimise mass injection rates and the risk of chlorine disinfection. This problem was solved by a non-dominated sorting genetic algorithm (NSGA-II). The proposed approach was demonstrated using the Phakalane network in Botswana. The results present robust booster chlorination (RBC) designs, which indicate the number of boosters, locations and injection rates in the network. The performance of RBC designs evaluated under uncertainty reveals lower risks of chlorine disinfection compared to deterministic-based designs. The proposed approach obtains booster chlorination designs that respond better to uncertainty in the operations of WDSs.

scholarly journals Development of Multi-Objective Optimal Redundant Design Approach for Multiple Pipe Failure in Water Distribution System

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 553 ◽  
Author(s):  
Young Choi ◽  
Joong Kim
Keyword(s):  
Optimal Design ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Search Algorithm ◽  
Harmony Search ◽  
Water Distribution Systems ◽  
Design Approach ◽  
Pipe Failure ◽  
Multi Objective

This study proposes a multi-objective optimal design approach for water distribution systems, considering mechanical system redundancy under multiple pipe failure. Mechanical redundancy is applied to the system’s hydraulic ability, based on the pressure deficit between the pressure requirements under abnormal conditions. The developed design approach shows the relationships between multiple pipe failure states and system redundancy, for different numbers of pipe-failure conditions (e.g., first, second, third, …, tenth). Furthermore, to consider extreme demand modeling, the threshold of the demand quantity is investigated simultaneously with multiple pipe failure modeling. The design performance is evaluated using the mechanical redundancy deficit under extreme demand conditions. To verify the proposed design approach, an expanded version of the well-known benchmark network is used, configured as an ideal grid-shape, and the multi-objective harmony search algorithm is used as the optimal design approach, considering construction cost and system mechanical redundancy. This optimal design technique could be used to propose a standard for pipe failure, based on factors such as the number of broken pipes, during failure condition analysis for redundancy-based designs of water distribution systems.

scholarly journals Multiobjective contaminant response modeling for water distribution systems security

2008 ◽  
Vol 10 (4) ◽  
pp. 267-274 ◽  
Author(s):  
Ami Preis ◽  
Avi Ostfeld
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Public Awareness ◽  
Water Distribution Systems ◽  
Evolutionary Model ◽  
Water Supply Systems ◽  
Nsga Ii ◽  
Drinking Water Distribution Systems ◽  
Conflicting Objectives ◽  
Operational Activities

Following the events of 9/11/2001 in the US, the world public awareness to possible terrorist attacks on water supply systems has increased significantly. The security of drinking water distribution systems has become a foremost concern around the globe. Water distribution systems are spatially diverse and thus are inherently vulnerable to intentional contamination intrusions. In this study, a multiobjective optimization evolutionary model for enhancing the response against deliberate contamination intrusions into water distribution systems is developed and demonstrated. Two conflicting objectives are explored: (1) minimization of the contaminant mass consumed following detection, versus (2) minimization of the number of operational activities required to contain and flush the contaminant out of the system (i.e. number of valves closure and hydrants opening). Such a model is aimed at directing quantitative response actions in opposition to the conservative approach of entire shutdown of the system until flushing and cleaning is completed. The developed model employs the multiobjective Non-Dominated Sorted Genetic Algorithm–II (NSGA-II) scheme, and is demonstrated using two example applications.

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