The Theory and Practice of Simulated Annealing

Henderson, Darrall; Jacobson, Sheldon H.; Johnson, Alan W.

doi:10.1007/0-306-48056-5_10

Cited by 346 publications

(218 citation statements)

References 103 publications

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“…For example, the size of the neighborhood should not be too small compared with the total solution space cardinality because the process might not occur sufficiently fast. Nevertheless, if the size of the neighborhood is too large, the algorithm might not be able to focus on specific areas (Henderson et al 2003). Adaptive neighborhoods have been proposed by several authors (Martins et al 2012;Yao 1993;Liu 1999) in which the size of the neighborhood changes according to the previously visited solutions.…”

Section: Working Principlesmentioning

confidence: 99%

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Simulated Annealing in Optimization of Energy Production in a Water Supply Network

Samora

Franca

Schleiss

et al. 2016

Water Resour Manage

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In water supply systems, the potential exists for micro-hydropower that uses the pressure excess in the networks to produce electricity. However, because urban drinking water networks are complex systems in which flows and pressure vary constantly, identification of the ideal locations for turbines is not straightforward, and assessment implies the need for simulation. In this paper, an optimization algorithm is proposed to provide a selection of optimal locations for the installation of a given number of turbines in a distribution network. A simulated annealing process was developed to optimize the location of the turbines by taking into account the hourly variation of flows throughout an average year and the consequent impact of this variation on the turbine efficiency. The optimization is achieved by considering the characteristic and efficiency curves of a turbine model for different impeller diameters as well as simulations of the annual energy production in a coupled hydraulic model. The developed algorithm was applied to the water supply system of the city Lausanne (Switzerland). This work focuses on the definition of the neighborhood of the simulated annealing process and the analysis of convergence towards the optimal solution for different restrictions and numbers of installed turbines.Water Resour Manage

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Section: Working Principlesmentioning

confidence: 99%

“…Adaptive neighborhoods have been proposed by several authors (Martins et al 2012;Yao 1993;Liu 1999) in which the size of the neighborhood changes according to the previously visited solutions. Finally, it was concluded that the neighborhood is heavily problem-specific (Henderson et al 2003).…”

Section: Working Principlesmentioning

confidence: 99%

Simulated Annealing in Optimization of Energy Production in a Water Supply Network

Samora

Franca

Schleiss

et al. 2016

Water Resour Manage

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“…GehadIsmail_FCI@yahoo.com Aboul Ella Hassanien aboitcairo@gmail.com 1 Faculty of Computers and Information, Cairo University, Cairo, Egypt 2 Scientific Research Group in Egypt (SRGE), Cairo, Egypt ever, this kind of modifications in SA schema does not usually inherit the ability of SA for escaping from local optima [11]. On the other hand, population-based meta-heuristics algorithms equipped with the ability to guide their search through using intelligent learning mechanism.…”

Section: B Gehad Ismail Sayedmentioning

confidence: 99%

A hybrid SA-MFO algorithm for function optimization and engineering design problems

Sayed

Hassanien

2018

Complex Intell. Syst.

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This paper presents a hybrid algorithm based on using moth-flame optimization (MFO) algorithm with simulated annealing (SA), namely (SA-MFO). The proposed SA-MFO algorithm takes the advantages of both algorithms. It takes the ability to escape from local optima mechanism of SA and fast searching and learning mechanism for guiding the generation of candidate solutions of MFO. The proposed SA-MFO algorithm is applied on 23 unconstrained benchmark functions and four well-known constrained engineering problems. The experimental results show the superiority of the proposed algorithm. Moreover, the performance of SA-MFO is compared with well-known and recent meta-heuristic algorithms. The results show competitive results of SA-MFO concerning MFO and other meta-heuristic algorithms.

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“…Marxan was originally conceived to solve a specific problem referred to as "the minimum set problem", in order to get some minimum representation of biodiversity resources for the lowest possible cost (Possingham el al., 2006). Marxan uses the simulated annealing algorithm, which is a local search algorithm (meta-heuristic) for global optimization problems (Henderson et al, 2003). The spatial optimization process built into Marxan, selects an optimal network of conservation sites that achieves conservation goals, minimizing a set of costs, by estimating, for each planning unit, the external design constraints and thus avoiding costly planning units (Lagrabrielle et al, 2010).…”

Section: Figura 7 Diferenças Do Valor De Conservação (Considerando Amentioning

confidence: 99%

Applying an integrated landscape characterization and evaluation tool to small islands (Pico, Azores, Portugal)

Fernandes¹,

Guiomar²,

Freire³

et al. 2014

RGCI

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Each landscape is determined and can be characterised by two types of environmental factors: stable biophysical characteristics and manageable land use patterns. The consideration of both these characterisation domains allows the definition of a homogeneous system of reference (the stable characteristics) with which every possible land use pattern can be compared through the use of common evaluation algorithms. The Integrated Landscape Assessment (ILA) concept builds a framework for data retrieval and evaluation processing that maximizes the following advantages: through the use of a stable reference system, it allows the comparative simulation of different land use scenarios, as well as the permanent availability of the same reference system, independently from the intensity of land use changes throughout the years. It also allows the use of different evaluation algorithms according to different evaluation contexts or paradigms, without having to repeat or adapt the characterisation process.The present paper illustrates the basic concepts on which ILA is based and developed as well as its application to ecological planning and systematic conservation planning in the Pico Island (Azores Archipelago).Keywords: Systematic conservation planning, integrated landscape assessment, GIS, Macaronesia. Resumo Cada território é determinado e pode ser caracterizado por dois tipos de factores ambientais: características biofísicas estáveis e padrões de uso do solo susceptíveis de gestão. A consideração destes dois domínios de caracterização permite a definição de um sistema de referência homogéneo (as características

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The Theory and Practice of Simulated Annealing

Cited by 346 publications

References 103 publications

Simulated Annealing in Optimization of Energy Production in a Water Supply Network

Simulated Annealing in Optimization of Energy Production in a Water Supply Network

A hybrid SA-MFO algorithm for function optimization and engineering design problems

Applying an integrated landscape characterization and evaluation tool to small islands (Pico, Azores, Portugal)

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