Single and multi-objective optimal design of water distribution systems: application to the case study of the Hanoi system

This manuscript describes the application of two recent methodologies developed by the authors for single and multi-objective optimal design of water distribution systems. The single-objective model is a hybrid algorithm incorporating decomposition, spanning tree search, and evolutionary computation, while the multi-objective algorithm integrates features form multi-objective genetic algorithms with the Cross Entropy combinatorial optimization scheme. The two models are implemented on the Hanoi water distribution system, one of the more explored systems in the research literature, through base runs and sensitivity analysis. The single-objective model produced the best known least cost solution for split pipe design, while the multi-objective model has shown robustness and well explanatory outcomes. Discussion of the accomplished results and suggestions for future research are provided.

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

Water ◽

10.3390/w11030553 ◽

2019 ◽

Vol 11 (3) ◽

pp. 553 ◽

Cited By ~ 4

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.

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Evolutionary Computation for Single and Multiobjective Water Distribution Systems Optimal Design

Handbook of Research on Hydroinformatics ◽

10.4018/978-1-61520-907-1.ch016 ◽

2010 ◽

pp. 332-345

Author(s):

Avi Ostfeld

Keyword(s):

Genetic Algorithm ◽

Optimal Design ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Future Research ◽

Research Directions ◽

Fixed Set ◽

Gradient Type ◽

Future Research Directions

Water distribution systems least cost pipe sizing/design is probably the most explored problem in water distribution systems optimization. Attracted numerous studies over the last four decades, two main approaches were employed: decomposition in which an “inner” linear programming problem is solved for a fixed set of flows/heads, while the flows/heads are altered at an “outer” problem using a gradient or a sub-gradient type technique; and the utilization of an evolutionary optimization algorithm (e.g., a genetic algorithm). In reality, however, from a broader perspective the design problem is inherently of a multiobjective nature incorporating competing objectives such as minimizing cost versus maximizing reliability. This chapter reviews some of the literature on single and multiobjective optimal design of water distribution systems and suggests a few future research directions in this area.

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Self-Adaptive Models for Water Distribution System Design Using Single-/Multi-Objective Optimization Approaches

Water ◽

10.3390/w11061293 ◽

2019 ◽

Vol 11 (6) ◽

pp. 1293 ◽

Cited By ~ 1

Author(s):

Choi ◽

Kim

Keyword(s):

Distribution System ◽

Distribution Systems ◽

Water Distribution ◽

Mathematical Problem ◽

Benchmark Problems ◽

Future Research ◽

Multi Objective Optimization ◽

Adaptive Approach ◽

Multi Objective ◽

Self Adaptive

This study compares the performance of self-adaptive optimization approaches in efficient water distribution systems (WDS) design and presents a guide for the selection of the appropriate method employing optimization utilizing the characteristic of each technique formulation. To this end, this study performs three types of analyses. First, the sensitivity analysis of each self-adaptive approach is conducted on single/multi-objective mathematical benchmark problems with various problem types (e.g., using solution shape or many local optimal solutions). Second, based on the applications and results of the mathematical problem, the performance of the algorithm is verified in the WDS design problem considering the minimum cost and the maximum system resilience under the single/multi-objective optimization framework. Third, the characteristics of search operators in the self-adaptive approach are compared according to the presence or absence of additional parameters and operators. Moreover, various performance indices are employed to compare the quantitative evaluation of each algorithm. Each algorithm is found to exhibit different characteristics depending on the problem scale and solution type. These results are expected to benefit future research in the formulation of new approaches and developments. Hence, this study provides rigorous testing of the performance of newly proposed algorithms in a highly simplified manner.

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A New Energy Optimization Strategy for Pumping Operation in Water Distribution Systems

Volume 6: Energy, Parts A and B ◽

10.1115/imece2012-86463 ◽

2012 ◽

Author(s):

Dhafar Al-Ani ◽

Saeid Habibi

Keyword(s):

Distribution System ◽

Energy Cost ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution System ◽

Water Distribution Systems ◽

Energy Optimization ◽

Operating Conditions ◽

Optimization Strategy ◽

Multi Objective

As time goes on, more and more operating-modes based on changing demand profiles will be compiled to enrich the range of feasible solutions for a water distribution system. This implies the conservation of energy consumed by a water pumping station and improves the ability for energy optimization. Another important goal was improving safety, reliability, and maintenance cost. In this paper, three important goals were addressed: cost-effectives, safety, and self-sustainability operations of water distribution systems. In this work, the objective functions to optimize were total electrical energy cost, maintenance costs, and reservoir water level variation while preserving the service provided to water clients. To accomplish these goals, an effective Energy Optimization Strategy (EOS) that manages trade-off among operational cost, system safety, and reliability was proposed. Moreover, the EOS aims at improving the operating conditions (i.e., pumping schedule) of an existing network system (i.e., with given capacities of tanks) and without physical changes in the infrastructure of the distribution systems. The new strategy consisted of a new Parallel Multi-objective Particle Swarm optimization with Adaptive Search-space Boundaries (P-MOPSO-ASB) and a modified EPANET. This has several advantages: obtaining a Pareto-front with solutions that are quantitatively equally good and providing the decision maker with the opportunity to qualitatively compare the solutions before their implementation into practice. The multi-objective optimization approach developed in this paper follows modern applications that combine an optimization algorithm with a network simulation model by using full hydraulic simulations and distributed demand models. The proposed EOS was successfully applied to a rural water distribution system, namely Saskatoon West. The results showed that a potential for considerable cost reductions in total energy cost was achieved (approximately % 7.5). Furthermore, the safety and the reliability of the system are preserved by using the new optimal pump schedules.

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Water Quality Based Multi-objective Optimal Design of Water Distribution Systems

Water Resources Management ◽

10.1007/s11269-016-1512-6 ◽

2016 ◽

Vol 31 (1) ◽

pp. 93-108 ◽

Cited By ~ 16

Author(s):

Meisam Shokoohi ◽

Massoud Tabesh ◽

Sara Nazif ◽

Mehdi Dini

Keyword(s):

Water Quality ◽

Optimal Design ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Multi Objective

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Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

Water ◽

10.3390/w10030307 ◽

2018 ◽

Vol 10 (3) ◽

pp. 307 ◽

Cited By ~ 33

Author(s):

Helena Mala-Jetmarova ◽

Nargiz Sultanova ◽

Dragan Savic

Keyword(s):

System Design ◽

Distribution System ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Research Field ◽

Future Research ◽

Comprehensive Information ◽

Primary Focus ◽

The Cost

Optimisation of water distribution system design is a well-established research field, which has been extremely productive since the end of the 1980s. Its primary focus is to minimise the cost of a proposed pipe network infrastructure. This paper reviews in a systematic manner articles published over the past three decades, which are relevant to the design of new water distribution systems, and the strengthening, expansion and rehabilitation of existing water distribution systems, inclusive of design timing, parameter uncertainty, water quality, and operational considerations. It identifies trends and limits in the field, and provides future research directions. Exclusively, this review paper also contains comprehensive information from over one hundred and twenty publications in a tabular form, including optimisation model formulations, solution methodologies used, and other important details.

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Multi-Objective Cuckoo Search for the Optimal Design of Water Distribution Systems

Civil Engineering and Urban Planning 2012 ◽

10.1061/9780784412435.072 ◽

2012 ◽

Cited By ~ 4

Author(s):

Q. Wang ◽

S. Liu ◽

H. Wang ◽

D. A. Savić

Keyword(s):

Optimal Design ◽

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Cuckoo Search ◽

Multi Objective

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

Water ◽

10.3390/w13101334 ◽

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.

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