Optimization Model for Water Distribution System Design

Lansey, Kevin; Mays, Larry W.

doi:10.1061/(asce)0733-9429(1989)115:10(1401)

Cited by 196 publications

(89 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This definition has been used frequently in early literature as shown by Lansey & Mays (1989) who report that several optimisation models have been developed with cost minimisation as the single objective of water distribution system design.…”

Section: Water Distribution System Design and Optimisationmentioning

confidence: 99%

Optimal Reliability-Based Design of Bulk Water Supply Systems

Chang

Zyl

2014

J. Water Resour. Plann. Manage.

View full text Add to dashboard Cite

DJ :;sc rt(l 1I UIl s uhnlltt ed In p a rt i~l fulfi lm en t o~' th e reqlllrcrnen ts fu r tht., degree ofM~s t e r ofSClence In Enginee ring AbstractBulk water supply systems are usually designed according to deterministic design guidelines. In South Africa, design guidelines specify that a bulk storage reservoir should have a storage capacity of 48 hours of annual average daily demand (AADD), and the feeder pipe a capacity of 1.5 times AADD (CSIR, 2000). Nel & Haarhoff (1996) proposed a stochastic analysis method that allowed the reliability of a reservoir to be estimated based on a Monte Carlo analysis of consumer demand, fire water demand and pipe failures. Van Zyl et al. (2008) developed this method further and proposed a design criterion of one failure in ten years under seasonal peak conditions.In this study, a method for the optimal design of bulk water supply systems is proposed with the design variables being the configuration of the feeder pipe system, the feeder pipe diameters (i.e. capacity), and the size of the bulk storage reservoir. The stochastic analysis method is applied to determine a trade-off curve between system cost and reliability, from which the designer can select a suitable solution.Optimisation of the bulk system was performed using the multi-objective genetic algorithm, NSGA-II. As Monte Carlo sampling can be computationally expensive, especially when large numbers of simulations are required in an optimisation exercise, a compression heuristic was implemented and refined to reduce the computational effort required of the stochastic simulation. Use of the compression heuristic instead of full Monte Carlo simulation in the reliability analysis achieved computational time savings of around 75% for the optimisation of a typical system.Application of the optimisation model showed that it was able to successfully produce a set of Pareto-optimal solutions ranging from low reliability, low cost solutions to high reliability, high cost solutions. The proposed method was first applied to a typical system, resulting in an optimal reservoir size of approximately 22 h AADD and feeder pipe capacity of 2 times AADD. This solution achieved 9% savings in total system cost compared to the South African design guidelines. In addition, the optimal solution proved to have better reliability that one designed according to South African guidelines.A sensitivity analysis demonstrated the effects of changing various system and stochastic parameters from typical to low and high values. The sensitivity results revealed that the length of the feeder pipe system has the greatest impact on both the cost and reliability of the bulk system. It was also found that a single feeder pipe is optimal in most cases, and that parallel feeder pipes are only optimal for short feeder pipe lengths.The optimisation model is capable of narrowing down the search region to a handful of possible design solutions, and can thus be used by the engineer as a tool to assist with the design of the final system.

show abstract

Section: Water Distribution System Design and Optimisationmentioning

confidence: 99%

Optimal Reliability-Based Design of Bulk Water Supply Systems

Chang

Zyl

2014

J. Water Resour. Plann. Manage.

View full text Add to dashboard Cite

show abstract

“…Various researchers (Walski 1985;Goulter 1987;Walters 1988;Mays 1989a andGoulter 1992) have made comprehensive reviews on the traditional methods. Early research on the optimization of water distribution systems used a linear programming technique.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other traditional optimization techniques including direct search techniques, dynamic programming, integer programming, and enumerative methods were applied to the optimal design of a water distribution system. A detailed review was given by Lansey and Mays (1989a) on these traditional optimization techniques. Su et al (1987) integrated a generalized reduced gradient (GRG) technique with a hydraulic network solver KYPIPE.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Competent Genetic-Evolutionary Optimization of Water Distribution Systems

Simpson

2001

J. Comput. Civ. Eng.

147

View full text Add to dashboard Cite

A genetic algorithm (GA) has been applied to the optimal design and rehabilitation of a water distribution system. Many of the previous applications have been limited to small water distribution systems, where the computer time used for solving the problem has been relatively small. In order to apply genetic and evolutionary optimization technique to a large-scale water distribution system, this paper employs one of competent genetic-evolutionary algorithms  a messy genetic algorithm to enhance the efficiency of an optimization procedure. Maximum flexibility is ensured by the formulation of a string and solution representation scheme, a fitness definition and the integration of a well-developed hydraulic network solver that facilitate the application of a genetic algorithm to the optimization of a water distribution system. Two benchmark problems of water pipeline design and a real water distribution system are presented to demonstrate the application of the improved technique. The results obtained show that the number of the design trials required by the messy genetic algorithm is consistently fewer than the other genetic algorithms.

show abstract

“…The conversion of continuous solutions into discrete diameters can induce a loss of optimality and even a loss of feasibility. Readers interested in previous work regarding the split-pipe design and continuous diameter approaches are referred to Walski (1985) and Lansey and Mays (1989).…”

Section: Introductionmentioning

confidence: 99%

Tabu search algorithms for water network optimization

Cunha

Ribeiro²

2004

European Journal of Operational Research

124

View full text Add to dashboard Cite

In this paper we propose a tabu search algorithm to find the least-cost design of looped water distribution networks. The mathematical nature of this optimization problem, a nonlinear mixed integer problem, is at the origin of a multitude of contributions to the literature in the last 25 years. In fact, exact optimization methods have not been found for this type of problem, and, in the past, classical optimization methods, like linear and nonlinear programming, were tried at the cost of drastic simplifications. Tabu search is a valuable heuristic technique for solving problems cast in combinatorial form. This is based on the human memory process and uses an iterative neighborhood search procedure in an attempt to avoid becoming trapped in local optima. The use of such a heuristic procedure to solve the aforementioned problem needs particular tailoring to produce high quality solutions. In this paper we present the essential features of the algorithm and the results obtained when it is applied to some of the classical water distribution network case studies appearing in the literature. The results are very promising and demonstrate the usefulness of tabu search algorithms in solving this kind of optimization problem.

show abstract

Optimization Model for Water Distribution System Design

Cited by 196 publications

References 11 publications

Optimal Reliability-Based Design of Bulk Water Supply Systems

Optimal Reliability-Based Design of Bulk Water Supply Systems

Competent Genetic-Evolutionary Optimization of Water Distribution Systems

Tabu search algorithms for water network optimization

Contact Info

Product

Resources

About