Search results for "Mathematical optimization"
showing 10 items of 1300 documents
Improvement of Statistical Decisions under Parametric Uncertainty
2011
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision‐making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the i…
Fast Nash Hybridized Evolutionary Algorithms for Single and Multi-objective Design Optimization in Engineering
2014
Evolutionary Algorithms (EAs) are one of advanced intelligent systems and they occupied an important position in the class of optimizers for solving single-objective/reverse/inverse design and multi-objective/multi physics design problems in engineering. The chapter hybridizes the Genetic Algorithms (GAs) based computational intelligent system (CIS) with the concept of Nash-Equilibrium as an optimization pre-conditioner to accelerate the optimization procedure. Hybridized GAs and simple GAs are validated through solving five complex single-objective and multi-objective mathematical design problems. For real-world design problems, the hybridized GAs (Hybrid Intelligent System) and the origin…
Representation and estimation of spectral reflectances using projection on PCA and wavelet bases
2008
In this article, we deal with the problem of spectral reflectance function representation and estimation in the context of multispectral imaging. Because the reconstruction of such functions is an inverse problem, slight variations in input data completely skew the expected results. Therefore, stabilizing the reconstruction process is necessary. To do this, we propose to use wavelets as basis functions, and we compare those with Fourier and PCA bases. We present the idea and compare these three methods, which belong to the class of linear models. The PCA method is training-set dependent and confirms its robustness when applied to reflectance estimation of the training sets. Fourier and wave…
Fitness diversity based adaptation in Multimeme Algorithms:A comparative study
2007
This paper compares three different fitness diversity adaptations in multimeme algorithms (MmAs). These diversity indexes have been integrated within a MmA present in literature, namely fast adaptive memetic algorithm. Numerical results show that it is not possible to establish a superiority of one of these adaptive schemes over the others and choice of a proper adaptation must be made by considering features of the problem under study. More specifically, one of these adaptations outperforms the others in the presence of plateaus or limited range of variability in fitness values, another adaptation is more proper for landscapes having distant and strong basins of attraction, the third one, …
An Introduction to Kernel Methods
2009
Machine learning has experienced a great advance in the eighties and nineties due to the active research in artificial neural networks and adaptive systems. These tools have demonstrated good results in many real applications, since neither a priori knowledge about the distribution of the available data nor the relationships among the independent variables should be necessarily assumed. Overfitting due to reduced training data sets is controlled by means of a regularized functional which minimizes the complexity of the machine. Working with high dimensional input spaces is no longer a problem thanks to the use of kernel methods. Such methods also provide us with new ways to interpret the cl…
A hybrid genetic algorithm with local search: I. Discrete variables: optimisation of complementary mobile phases
2001
Abstract A hybrid genetic algorithm was developed for a combinatorial optimisation problem. The assayed hybridation modifies the reproduction pattern of the genetic algorithm through the application of a local search method, which enhances each individual in each generation. The method is applied to the optimisation of the mobile phase composition in liquid chromatography, using two or more mobile phases of complementary behaviour. Each of these phases concerns the optimal separation of certain compounds in the analysed mixture, while the others can remain overlapped. This optimisation approach may be useful in situations where full resolution with a single mobile phase is unfeasible. The o…
Efecto Bullwhip y restricciones de capacidad productiva en las cadenas colaborativas
2008
El objetivo del presente artículo es profundizar en el análisis de Evans y Naim (1) sobre la relación entre la capacidad de limitada producción y el efecto bullwhip, y actualizarlo en función de las recientes configuraciones de cadenas de suministro colaborativas. Se analizan tres cadenas de suministro con capacidad de producción limitada: la misma cadena de suministro tradicional estudiada por Evans y Naim (1), una cadena EPOS (Exchange Point of Sales) y una cadena sincronizada. Se adopta un sistema de métricas para evaluar los beneficios de los nodos de la cadena medidos en términos de estabilidad de la orden de pedido, estabilidad de los inventarios, y robustez del sistema, y en términos…
Designing portfolios of financial products via integrated simulation and optimization models
1999
We analyze the problem of debt issuance through the sale of innovative financial products. The problem is broken down to questions of designing the financial products, specifying the debt structure with the amount issued in each product, and determining an optimal level of financial leverage. We formulate a hierarchical optimization model to integrate these three issues and provide constructive answers. Input data for the models are obtained from Monte Carlo simulation procedures that generate scenarios of holding period returns of the designed products. The hierarchical optimization model is specialized for the problem of issuing a portfolio of callable bonds to fund mortgage assets. The …
Physics Contributions Evaluation of interpolation methods for TG-43 dosimetric parameters based on comparison with Monte Carlo data for high-energy b…
2010
Purpose: The aim of this work was to determine dose distributions for high-energy brachytherapy sources at spa- tial locations not included in the radial dose function gL(r) and 2D anisotropy function F(r,θ) table entries for radial dis- tance r and polar angle θ. The objectives of this study are as follows: 1) to evaluate interpolation methods in order to accurately derive gL(r) and F(r,θ) from the reported data; 2) to determine the minimum number of entries in gL(r) and F(r,θ) that allow reproduction of dose distributions with sufficient accuracy. Material and methods: Four high-energy photon-emitting brachytherapy sources were studied: 60Co model Co0.A86, 137Cs model CSM-3, 192Ir model I…
Designing Paper Machine Headbox Using GA
2003
Abstract A non-smooth biobjective optimization problem for designing the shape of a slice channel in a paper machine headbox is described. The conflicting goals defining the optimization problem are the ones determining important quality properties of produced paper: 1) basis weight should be even and 2) the wood fibers of paper should mainly be oriented to the machine direction across the width of the whole paper machine. The novelty of the considered approach is that maximum deviations are used instead of least squares when objective functions are formed. For the solution of this problem, a multiobjective genetic algorithm based on nondominated sorting is considered. The numerical results…