Tabu search algorithms for water network optimization

Cunha, Maria da Conceição; Ribeiro, Luísa

doi:10.1016/s0377-2217(03)00242-x

Cited by 124 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A group of these techniques apply evolutionary algorithms (Savic & Walters 1997;Cunha & Ribeiro 2004) that, despite their capacity to evaluate tens of thousands of solutions, are not free from the above-mentioned drawbacks. Also, they seem to be limited by the computer time load for actual large networks.…”

Section: Notationmentioning

confidence: 99%

Quantifying the economy of flow distribution in water supply looped networks

Martínez

2011

Journal of Hydroinformatics

View full text Add to dashboard Cite

Optimization of water supply looped networks has attracted a great deal of attention from researchers for more than 30 years. As the classical water supply looped network optimization problem is mathematically non-convex and multimodal, the resulting solution of most approaches is uncertain in the sense of how close it is to the ''best'' solution. In many cases, this ''best''' or ''global'' solution is invoked and pursued only intuitively without a clear understanding of its meaning. This paper discusses what is involved in ''global'' solutions and the role that pipe flow distribution can play to deal with non-convexity and multimodality in a new context. The author has introduced this new context recently after formulating a new objective function capable of finding a looped network that can be economically more attractive than its related branched one. Therefore, the convenience of an approach dealing with flows and heads, as relevant decision variables, is encouraged in this paper and its advantages enumerated under the new concepts.The entropy approach is studied critically and an example is provided for comparison with the proposed approach.

show abstract

Section: Notationmentioning

confidence: 99%

Quantifying the economy of flow distribution in water supply looped networks

Martínez

2011

Journal of Hydroinformatics

View full text Add to dashboard Cite

show abstract

“…Simulated annealing was applied by Loganathan et al (1995), and by Cunha and Sousa (1999). Tabu searches were employed by Fanni et al (2000), and by Da Conceicao Cunha and Ribeiro (2004). Simpson et al (2001) were the first to apply Ant Colony Optimization (ACO) to WDS optimization in 2001.…”

Section: Concise Survey Of Literaturementioning

confidence: 99%

Robust multi‐objective optimization for water distribution system design using a meta‐metaheuristic

Raad

Sinske²,

Vuuren

2009

Int Trans Operational Res

View full text Add to dashboard Cite

The design of an urban water distribution system (WDS) is a challenging problem involving multiple objectives. The goal of robust multi-objective optimization for WDS design is to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. In addition to satisfying consumer needs, a system must be built to accommodate multiple demand loading conditions, withstand component failures and allow surplus capacity for growth. In a developmental setting, WDS robustness becomes even more crucial, owing to the limited availability of resources, especially for maintenance. Recent optimization studies have achieved success using multi-objective evolutionary algorithms, such as the Non-dominated Sorting Genetic Algorithm II (NSGA-II). However, the multi-objective design of a large WDS within a reasonable timeframe remains a formidable problem, owing to the extremely high computational complexity of the problem. In this paper, a meta-algorithm called AMALGAM is applied for the first time to WDS design. AMALGAM uses multiple metaheuristics simultaneously in an attempt to improve optimization performance. Additionally, a Jumping-gene Genetic Algorithm (NSGA-II-JG) is also applied for the first time to WDS design. These two algorithms were tested against some other metaheuristics (including NSGA-II and a new greedy algorithm) with respect to a number of benchmark systems documented in the literature, and AMALGAM demonstrated the best performance overall, while NSGA-II-JG fared worse than the ordinary NSGA-II. Large cost savings and reliability improvements are demonstrated for a real WDS developmental case study in South Africa.

show abstract

“…These techniques employ heuristics to traverse large search spaces and find near-optimal solutions. Several approaches like genetic programming [6,7], tabu search [8], shuffled frogs [9], etc. fall in the wide umbrella of meta-heuristics.…”

Section: Introductionmentioning

confidence: 99%

“…Pumps were the earliest component to be considered during network optimization, in addition to the selection of pipe diameters, although they were restricted to a single pump at the source [10]. Tanks and valves were incorporated within meta-heuristic frameworks [6,8,9]. The networks considered in these studies are urban, where the role of tanks is to act as buffers to be used during periods of high demand.…”

Section: Introductionmentioning

confidence: 99%

A Series of ILP models for the optimization of water distribution networks

2019

View full text Add to dashboard Cite

The design of rural drinking water schemes consists of optimization of several network components like pipes, tanks, pumps and valves. The sizing and configuration of these network configurations need to be such that the water requirements are met while at the same time being cost efficient so as to be within government norms. We developed the JalTantra system to design such water distribution networks. The Integer Linear Program (ILP) model used in JalTantra and described in our previous work solved the problem optimally, but took a significant amount of time for larger networks-an hour for a network with 100 nodes. In this current work, we describe a series of three improvements of the model. We prove that these improvements result in tighter models, i.e. the set of points of linear relaxation is strictly smaller than the linear relaxation for the initial model. We test the series of three improved models along with the initial model over eight networks of various sizes and show a distinct improvement in performance. The 100-node network now takes only 49 s to solve. These changes have been implemented in JalTantra, resulting in a system that can solve the optimization of real world rural drinking water networks in a matter of seconds. The JalTantra system is free for use, and is available at https://www.cse.iitb.ac.in/jaltantra/.

show abstract

Tabu search algorithms for water network optimization

Cited by 124 publications

References 22 publications

Quantifying the economy of flow distribution in water supply looped networks

Quantifying the economy of flow distribution in water supply looped networks

Robust multi‐objective optimization for water distribution system design using a meta‐metaheuristic

A Series of ILP models for the optimization of water distribution networks

Contact Info

Product

Resources

About