Practical Considerations for Simulated Annealing Implementation

Ledesma, Sergio; Aviña, Gabriel; Sánchez, Raúl

doi:10.5772/5560

Cited by 42 publications

(33 citation statements)

References 3 publications

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“…The algorithm proceeds by decreasing the temperature till it converges to minimum. Here we used Mathematica 10 to employ the procedure, but the interested readers can read the details of simulated annealing from ref [35]. Training of network will lead us to the final values of network adaptive coefficients that will be replaced in Eq.…”

Section: Lsann Formulation For Fractional Differential Equationsmentioning

confidence: 99%

A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation

Khan

Shaikh

Raja

et al. 2016

Journal of Applied Mathematics, Statistics and Informatics

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In this article, Legendre simulated annealing, neural network (LSANN) is designed for fuzzy fractional order differential equations, which is employed on fractional fuzzy initial value problem (FFIVP) with triangular condition. Here, Legendre polynomials are used to modify the structure of neural networks with a Taylor series approximation of the tangent hyperbolic as activation function while the network adaptive coefficients are trained in the procedure of simulated annealing to optimize the residual error. The computational results are depicted in terms of numerical values to compare them with previous results.

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Section: Lsann Formulation For Fractional Differential Equationsmentioning

confidence: 99%

A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation

Khan

Shaikh

Raja

et al. 2016

Journal of Applied Mathematics, Statistics and Informatics

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“…, are simulated annealing solutions to a linear scheduling problem. Afterwards, the algorithm duration-gradient process is established as per Ledesma et al [15] in…”

Section: System Implementationmentioning

confidence: 99%

“…Duration values are discrete values selected based on a definitive convergence-gradient algorithm, which will be presented later. In order to enhance simulated annealing efficiency, a definitive number of iterative processes at each duration level are generated as per Ledesma et al [15] in = { 1, , 2, , 3, , . .…”

Section: System Implementationmentioning

confidence: 99%

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An Integrated Expert System for Linear Scheduling Heavy Earthmoving Operations

Markiz

Jrade

2016

Journal of Construction Engineering

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Heavy earthmoving operations are repetitive in nature and vulnerable to time-related restraints and uncertainties. Therefore, at the conceptual stage, scheduling these operations can take a linear form, known as linear schedule or line of balance (LOB). In such type of work, generating a preliminary line of balance for variable sequencing of activities is crucial. In this paper, an integrated expert system for determining preliminary linear schedules for heavy earthmoving operations at the conceptual stage is presented. The proposed system incorporates numerous factors that influence the analysis of earthmoving operations, which include geological and topographical parameters used to determine productivity rates at the conceptual stage. Also, the proposed system is capable of automatically generating a line of balance based on a stochastic scheduling technique via the metaheuristic simulated annealing intelligent approach to incorporate randomness and uncertainties in performing the associated activities. A parametric analysis is conducted in order to quantify the system's degree of accuracy. An actual case project is then utilized to illustrate its numerical capabilities. Generating accurate linear schedules for heavy earthmoving operations at the conceptual design stage is anticipated to be of major significance to infrastructure project stakeholders, engineers, and construction managers by detecting schedule's conflicts early in order to enhance overall operational logistics.

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“…According to that and considering previous works related to this topic [5][6][7], the authors propose an optimization methodology based on heuristic approaches. More specifically, the authors have developed a numerical model based on Simulated Annealing [8][9][10][11][12][13] since this formulation can include natively continuum and discrete design variables and it obtains optimal solutions for real cases in an acceptable computing time.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Structural optimization of high voltage transmission line towers considering continuum and discrete design variables

Par¹,

Mart²,

ñez³

et al. 2012

WIT Transactions on the Built Environment

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Structural optimization has been usually applied to singular projects (e.g. a dam) and/or to common designs largely repeated (e.g. automotive components), and high voltage transmission towers can be included in both groups since they are expensive and a large number of them is required.In this paper, the authors propose a general formulation for obtaining the structural optimum design of latticed high voltage towers. The formulation is devoted to obtaining the most common objective in engineering (minimum cost) considering the limitations imposed in actual norms for this kind of structure. According to this idea, real applications are studied and modeled under real conditions (e.g. loads, constraints, building process). Constructive aspects like the specific geometry, the structural elements or the building process are specifically considered. The optimization model proposed also deals with continuum design variables (global geometry variables) and discrete design variables (area, inertia and/or cross section dimensions, for example) both together. The use of both types of design variables is crucial for defining a realistic model that can be used in practical applications in engineering. The optimum design formulation proposed is general and can be easily applied to other different types of 3D latticed structures.Finally, a real application example of a high voltage tower under real conditions and requirements is analyzed.

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Practical Considerations for Simulated Annealing Implementation

Cited by 42 publications

References 3 publications

A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation

A Neural Computational Intelligence Method Based on Legendre Polynomials for Fuzzy Fractional Order Differential Equation

An Integrated Expert System for Linear Scheduling Heavy Earthmoving Operations

Structural optimization of high voltage transmission line towers considering continuum and discrete design variables

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