An iterated local search algorithm for water distribution network design optimization

Corte, Annelies De; Sörensen, Kenneth

doi:10.1002/net.21673

Cited by 32 publications

(25 citation statements)

References 35 publications

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“…During this process, simple methods should not be forgotten. Quite often, overly complex strategies are developed for problems where much simpler techniques perform equally well .…”

Section: Tsplib Benchmarkmentioning

confidence: 99%

“…During this process, simple methods should not be forgotten. Quite often, overly complex strategies are developed for problems where much simpler techniques perform equally well [29]. JAMES reduces the effort needed by researchers and practitioners to experiment with various well-known local search strategies and components, facilitating iterative refinement from a simple starting point, e.g.…”

Section: Tsplib Benchmarkmentioning

confidence: 99%

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JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

et al. 2016

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Summary This paper describes the Java Metaheuristics Search framework (JAMES, v1.1): an object‐oriented Java framework for discrete optimization using local search algorithms that exploits the generality of such metaheuristics by clearly separating search implementation and application from problem specification. A wide range of generic local searches are provided, including (stochastic) hill climbing, tabu search, variable neighbourhood search and parallel tempering. These can be applied to any user‐defined problem by plugging in a custom neighbourhood for the corresponding solution type. Using an automated analysis workflow, the performance of different search algorithms can be compared in order to select an appropriate optimization strategy. Implementations of specific components are included for subset selection, such as a predefined solution type, generic problem definition and several subset neighbourhoods used to modify the set of selected items. Additional components for other types of problems (e.g. permutation problems) are provided through an extensions module which also includes the analysis workflow. In comparison with existing Java metaheuristics frameworks that mainly focus on population‐based algorithms, JAMES has a much lower memory footprint and promotes efficient application of local searches by taking full advantage of move‐based evaluation. Releases of JAMES are deployed to the Maven Central Repository so that the framework can easily be included as a dependency in other Java applications. The project is fully open source and hosted on GitHub. More information can be found at http://www.jamesframework.org. Copyright © 2016 John Wiley & Sons, Ltd.

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“…During this process, simple methods should not be forgotten. Quite often, overly complex strategies are developed for problems where much simpler techniques perform equally well .…”

Section: Tsplib Benchmarkmentioning

confidence: 99%

Section: Tsplib Benchmarkmentioning

confidence: 99%

JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

et al. 2016

View full text Add to dashboard Cite

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“…A variety of facility location problems arise in supply chain management and most of them are combinatorial in nature (Blum and Roli, 2003;Ardjmand et al, 2014;De Corte and Sörensen, 2015;Cerrone et al, 2017;De Armas et al, 2017). The location problems have several industrial applications.…”

Section: Introductionmentioning

confidence: 99%

A simple multi-wave algorithm for the uncapacitated facility location problem

Glover¹,

Hanafi²,

Guemri³

et al. 2018

Front. Eng

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The multi-wave algorithm (Glover, 2016) integrates tabu search and strategic oscillation utilizing repeated waves (nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers' demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.

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“…The advantages of this method lie in the small number of network evaluations and the fact that it does not need to bear the global objective in mind (but is concerned with local changes of cells), although the optimality of the final solution and the change of flow directions are possible weaknesses. Furthermore, other nonpopulation-based metaheuristic optimization methods such as iterated local search (ILS) [52] and variable neighborhood search (VNS) [53] have also recently arisen in the domain of WDN optimization.…”

Section: ) Nonpopulation-based Metaheuristicsmentioning

confidence: 99%

Optimization of Potable Water Distribution and Wastewater Collection Networks: A Systematic Review and Future Research Directions

Zhao

Beach

Rezgui

2016

IEEE Trans. Syst. Man Cybern, Syst.

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Abstract-Potable water distribution networks (WDNs) and wastewater collection networks (WWCNs) are the two fundamental constituents of the complex urban water infrastructure. Such water networks require adapted design interventions as part of retrofitting, extension and maintenance activities. Consequently, proper optimization methodologies are required to reduce the associated capital cost while also meeting the demands of acquiring clean water and releasing wastewater by consumers. In this paper, a systematic review of the optimization of both WDNs and WWCNs, from the preliminary stages of development through to the state-of-the-art, is jointly presented. Firstly, both WDNs and WWCNs are conceptually and functionally described along with illustrative benchmarks. The optimization of water networks across both clean and waste domains is then systematically reviewed and organized, covering all levels of complexity from the formulation of cost functions and constraints, through to traditional and advanced optimization methodologies. The rationales behind employing these methodologies as well as their advantages and disadvantages are investigated. The paper then critically discusses current trends and identifies directions for future research by comparing the existing optimization paradigms within WDNs and WWCNs and proposing common research directions for optimizing water networks. Optimization of urban water networks is a multidisciplinary domain, within which this paper is anticipated to be of great benefit to researchers and practitioners.

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An iterated local search algorithm for water distribution network design optimization

Cited by 32 publications

References 35 publications

JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

JAMES: An object‐oriented Java framework for discrete optimization using local search metaheuristics

A simple multi-wave algorithm for the uncapacitated facility location problem

Optimization of Potable Water Distribution and Wastewater Collection Networks: A Systematic Review and Future Research Directions

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