Optimization of Pumping Schedules Using the Genealogical Decision Tree Approach

This paper examines the application of a particle filtering-based optimization technique, the genealogical decision trees (GDT), to a finite horizon pump scheduling problem in a water distribution network. The GDT approach for trajectory tracking is first introduced, and a modified algorithm for minimization of costs during pump sequence optimization is then presented. Several variants of the algorithm are suggested, using the extended end constraint and neutrality. The performance of the optimization in various algorithm and parameter settings is examined in extensive simulations. It was observed that both the extended end constraint and neutrality improved the performance, however the deviation between solutions within a population and between different runs remained uncomfortably large. Finally, a comparison with a number of alternative up-to-date optimization techniques is provided. It was observed that the performance of GDT was adequate, compared with the best available approaches.

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Proposal of optimal operation strategy applied to water distribution network with statistical approach

Ambiente e Agua - An Interdisciplinary Journal of Applied Science ◽

10.4136/ambi-agua.2455 ◽

2020 ◽

Vol 15 (2) ◽

pp. 1

Author(s):

Alex Takeo Yasumura Lima Silva ◽

Fernando Das Graças Braga da Silva ◽

André Carlos da Silva ◽

José Antonio Tosta dos Reis ◽

Claudio Lindemberg de Freitas ◽

...

Keyword(s):

Genetic Algorithms ◽

Water Distribution ◽

Distribution Network ◽

Water Distribution Network ◽

Distribution Networks ◽

Optimal Operation ◽

Optimization Techniques ◽

Experimental Techniques ◽

Computational Optimization ◽

Depth Analysis

Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using statistics and the design of experimental tools and software. The proposed technique was applied to a theoretical network developed for the study. Preliminary simulations were accomplished using EPANET, representing the main causes of water and energy inefficiency in Brazilian sanitation companies. Some parameters were changed in applying this model, such as reservoir level, pipe diameter, pumping pressures, and valve-closing percentage. These values were established by the design of experimental techniques. As output, we obtained the equation of response surface, optimized, which resulted in values of established hydraulic parameters. From these data, the obtained parameters in computational optimization algorithms were applied, resulting in losses of 26.61%, improvement of 16.19 p.p. with regard to the network without optimization, establishing an operational strategy involving three pumps and a pressure-reducing valve. We conclude that the association of optimization and the planning of experimental techniques constitutes an encouraging method to deal with the complexity of water-distribution network optimization.

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Chaos-Directed Genetic Algorithms for Water Distribution Network Design: An Enhanced Search Method

10.21203/rs.3.rs-574714/v1 ◽

2021 ◽

Author(s):

POOJITHA S. N ◽

Vinayakam Jothiprakash ◽

B. Sivakumar

Keyword(s):

Computational Efficiency ◽

Water Distribution ◽

Distribution Network ◽

Optimal Solution ◽

Water Distribution Network ◽

Optimization Techniques ◽

Benchmark Problems ◽

Directed Search ◽

Sequential Approach ◽

Water Distribution Network Design

Abstract The design of a water distribution network (WDN) is an ever-challenging problem. Development and application of optimization techniques for WDN design have been an important area of research. Recently, the introduction of chaos theory-based evolutionary algorithms (EAs) in addition to traditional random-based ones has elevated the scope for further improving the performance of EAs. The present study proposes a chaos-directed genetic algorithm (CDGA) by incorporating chaos ergodicity in GA mechanics for WDN optimal design. Two novel frameworks, the non-sequential approach (NSA) and sequential approach (SA) are introduced. The influence of chaotic systems with high dimensionality maps in improving the search efficacy of GA when compared to the low dimensionality maps is explored. Considering four widely studied WDN benchmark problems, the performance of the proposed GA and CDGA models is evaluated. From the results, it is observed that the CDGA models outperform GA with better search efficacy, requiring fewer function evaluations to locate the optimal solution. Also, concerning the different chaotic maps used in the present study to induce chaos ergodicity, the results highlight the usefulness of chaos-directed search in improving the computational efficiency of GA. From the computational results, the study suggests the usage of a chaotic system with other bio-inspired techniques for their improved search and computational efficiency.

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A Decision Tree Approach to the Risk Evaluation of Urban Water Distribution Network Pipes

Safety ◽

10.3390/safety6030036 ◽

2020 ◽

Vol 6 (3) ◽

pp. 36

Author(s):

Yanying Yang ◽

Yu Hu ◽

Jianchun Zheng

Keyword(s):

High Risk ◽

Decision Tree ◽

Water Supply ◽

Water Distribution ◽

Learning Algorithm ◽

Three Dimensional ◽

Water Distribution Network ◽

Dominant Factor ◽

High Rise ◽

Risk Rate

To evaluate the risk of a pipe in the water supply network of Beijing, we used the accident records of the gridding urban management (GUM) system. In addition, road and building information derived from a three-dimensional (3D) electronic map was also employed. A machine learning algorithm, the decision tree, was employed to train and evaluate the dataset. The results show that the contributions of the surrounding buildings and roads are neglectable, except for super-high-rise buildings, which have limited contributions. This finding is consistent with the results of other studies. The decision tree identifies dominant features and isolates the risk contribution of such features. The output tree structure indicated that the time since the last accident is a dominant factor, to which super-high-rise buildings contribute slightly. A cut-off value of 0.019 was chosen to predict high-risk regions. Approximately 0.4% of the data were predicted to be high risk, and the corresponding gain in risk rate was approximately 19.2. This model may be used in cities where detailed profiles of water supply pipes and maintenance records are not available or are expensive to achieve.

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Parameter Improvement of the Soccer League Competition Algorithm by Introducing Stubborn Players: Application to Water Distribution Network

Mathematical Problems in Engineering ◽

10.1155/2016/3425374 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 2

Author(s):

Godfrey Chagwiza ◽

Absalom Jaison ◽

Tavengwa Masamha

Keyword(s):

Water Distribution ◽

Distribution Network ◽

Water Distribution Network ◽

Distribution Networks ◽

Computational Results ◽

Optimal Cost ◽

Individual Player ◽

The Individual ◽

Modified Algorithm ◽

Better Than

A modified soccer league algorithm is presented in this paper. The effect of stubborn fixed players is investigated and the algorithm is implemented to three benchmark water distribution networks. The modified algorithm is compared to several algorithms. The results show that the modified algorithm performs better than the soccer league competition algorithm, in particular, on the average number of evaluations required to find the optimal cost. Computational results show that the utility benefit of both the individual player and team is essential. The algorithm becomes more reliable when utility benefits are high and as the number of fixed players increases.

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Design of water distribution systems using an intelligent simple benchmarking algorithm with respect to cost optimization and computational efficiency

Water Science & Technology Water Supply ◽

10.2166/ws.2019.065 ◽

2019 ◽

Vol 19 (7) ◽

pp. 1892-1898 ◽

Cited By ~ 5

Author(s):

Sachin Shende ◽

K. W. Chau

Keyword(s):

Distribution Systems ◽

Water Distribution ◽

Heuristic Algorithms ◽

Cost Optimization ◽

Minimum Cost ◽

Water Distribution Network ◽

Optimization Methods ◽

Optimization Techniques ◽

Hydraulic Simulation ◽

Optimum Solution

Abstract The increasing stress on the water distribution network (WDN) considering demand satisfaction with minimum cost has inspired designers to apply various optimization techniques to meet the consequent challenges. The traditional way of using optimization methods, e.g. stochastic meta-heuristic algorithms, have come along with various constraints to explore an optimum solution. In this study, a newly developed meta-heuristic algorithm called the Simple Benchmarking Algorithm (SBA) is used to optimize pipe size. A modified approach with SBA having interfaces with the EPANET 2.0 hydraulic simulation model is used to compute the minimum cost of the two-loop network and the Hanoi benchmark WDN. Results show that SBA is more efficient in obtaining the least possible cost with fast convergence.

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