Simulated Annealing

Bertsimas, Dimitris; Tsitsiklis, John N.

doi:10.1214/ss/1177011077

Cited by 872 publications

(464 citation statements)

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“…In this study, the most informative subsets of independent predictors (i.e., sensors) to be included in the final LDA models were chosen by applying a variable selection algorithm, since not all sensors present relevant information and so, their inclusion in the classification models may increase the noise effects. The best subsets of sensors (varying from 2 to 39) were established among the 40 potentiometric sensor signals using the SA variable selection algorithm [34][35][36]. The LDA potential was evaluated using two cross-validation (CV) variants: leave-one-out (LOO-CV), known to be an over-optimistic procedure; and, repeated K-fold (repeated K-fold-CV) technique.…”

Section: Discussionmentioning

confidence: 99%

Perception of olive oils sensory defects using a potentiometric taste device

Veloso

Silva

Rodrigues

et al. 2018

Talanta

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A B S T R A C TThe capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intraand inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (Pvalue = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.

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Section: Discussionmentioning

confidence: 99%

Perception of olive oils sensory defects using a potentiometric taste device

Veloso

Silva

Rodrigues

et al. 2018

Talanta

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“…Simulated annealing is a probabilistic method based on the process of heating of steel and ceramics and consists of a discrete-time inhomogeneous Markov chain (Bertsimas and Tsitsikis 1993). A Markov chain is a sequence of random variables in which each variable depends only on the state of the system in the previous iteration.…”

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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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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“…In the first set of case studies, we consider various (Q, L) combinations, including (1, 255), (2,242), (3,255), (4,624), and (6, 342), and set the ISI to 4 s and T R to 2 s. Following Kao et al [16], the reference waveform h * of model (2) is set to the double-gamma function of SPM, normalized to have a maximum of 1. The fMRI time series is assumed to have a second-order Legendre polynomial drift.…”

Section: Single-and Multi-objective Er-fmri Designsmentioning

confidence: 99%

A fast algorithm for constructing efficient event-related functional magnetic resonance imaging designs

Kao

Mittelmann

2013

Journal of Statistical Computation and Simulation

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We propose a novel, efficient approach for obtaining high-quality experimental designs for event-related functional magnetic resonance imaging (ER-fMRI), a popular brain mapping technique. Our proposed approach combines a greedy hill-climbing algorithm and a cyclic permutation method. When searching for optimal ER-fMRI designs, the proposed approach focuses only on a promising restricted class of designs with equal frequency of occurrence across stimulus types. The computational time is significantly reduced. We demonstrate that our proposed approach is very efficient compared with a recently proposed genetic algorithm approach. We also apply our approach in obtaining designs that are robust against misspecification of error correlations.

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Simulated Annealing

Cited by 872 publications

References 0 publications

Perception of olive oils sensory defects using a potentiometric taste device

Perception of olive oils sensory defects using a potentiometric taste device

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

A fast algorithm for constructing efficient event-related functional magnetic resonance imaging designs

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