Computational study of the step size parameter of the subgradient optimization method

The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

Optical Characterization and Optimization of Display Components : Some Applications to Liquid-Crystal-Based and Electrochromics-Based Devices

This dissertation is focused on theoretical and experimental studies of optical properties of materials and multilayer structures composing liquid crystal displays (LCDs) and electrochromic (EC) devices. By applying spectroscopic ellipsometry, we have determined the optical constants of thin films of electrochromic tungsten oxide (WOx) and nickel oxide (NiOy), the films’ thickness and roughness. These films, which were obtained at spattering conditions possess high transmittance that is important for achieving good visibility and high contrast in an EC device. Another application of the general spectroscopic ellipsometry relates to the study of a photo-alignment layer of a mixture of azo-dyes SD-1 and SDA-2. We have found the optical constants of this mixture before and after illuminating it by polarized UV light. The results obtained confirm the diffusion model to explain the formation of the photo-induced order in azo-dye films. We have developed new techniques for fast characterization of twisted nematic LC cells in transmissive and reflective modes. Our techniques are based on the characteristics functions that we have introduced for determination of parameters of non-uniform birefringent media. These characteristic functions are found by simple procedures and can be utilised for simultaneous determination of retardation, its wavelength dispersion, and twist angle, as well as for solving associated optimization problems. Cholesteric LCD that possesses some unique properties, such as bistability and good selective scattering, however, has a disadvantage – relatively high driving voltage (tens of volts). The way we propose to reduce the driving voltage consists of applying a stack of thin (~1µm) LC layers. We have studied the ability of a layer of a surface stabilized ferroelectric liquid crystal coupled with several retardation plates for birefringent color generation. We have demonstrated that in order to accomplish good color characteristics and high brightness of the display, one or two retardation plates are sufficient.

Comparison Of Demand Pattern Calibration In Water Distribution Networks With Geographic And Non-Geographic Parameterization

Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.

A Diagnostic Assessment Of Evolutionary Multiobjective Optimization For Water Resources Systems

This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective evolutionary algorithms (MOEAs) and highlights key advances that the water resources field can exploit to better discover the critical tradeoffs constraining our systems. This study provides the most comprehensive diagnostic assessment of MOEAs for water resources to date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of ten benchmark MOEAs for a representative suite of water resources applications addressing rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based water supply portfolio planning. The suite of problems encompasses a range of challenging problem properties including (1) many-objective formulations with 4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4) discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability (also called epistasis). The applications are representative of the dominant problem classes that have shaped the history of MOEAs in water resources and that will be dominant foci in the future. Recommendations are provided for which modern MOEAs should serve as tools and benchmarks in the future water resources literature.

Solving the non-convexity problem in some shopping-time and human-capital models

Several works in the shopping-time and in the human-capital literature, due to the nonconcavity of the underlying Hamiltonian, use Örst-order conditions in dynamic optimization to characterize necessity, but not su¢ ciency, in intertemporal problems. In this work I choose one paper in each one of these two areas and show that optimality can be characterized by means of a simple aplication of Arrowís (1968) su¢ ciency theorem.

Non-asymptotic confidence bounds for the optimal value of a stochastic program

We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimal space manoeuvres in a non-Keplerian force field

In this work the problem of a spacecraft bi-impulsive transfer between two given non coplanar elliptical orbits, with minimum fuel consumption, is solved considering a non-Keplerian force field (the perturbing forces include Earth gravity harmonics and atmospheric drag). The problem is transformed in the Two Point Boundary Value Problem. It is developed and implemented a new algorithm, that uses the analytical expressions developed here. A dynamics that considered a Keplerian force field was used to produce an initial guess to solve the Two Point Boundary Value Problem. Several simulations were performed to observe the spacecraft orbital behaviour by different kind of perturbations and constraints, on a fuel consumption optimization point of view. (C) 2002 COSPAR. Published by Elsevier B.V. Ltd. All rights reserved.

Non-newtonian heat transfer on a plate heat exchanger with generalized configurations

For the configuration optimization of plate heat exchangers (PHEs), the mathematical models for heat transfer and pressure drop must be valid for a wide range of operational conditions of all configurations of the exchanger or the design results may be compromised. In this investigation, the thermal model of a PHE is adjusted to fit experimental data obtained from non-Newtonian heat transfer for eight different configurations, using carboxymethylcellulose solutions (CMC) as test fluid. Although it is possible to successfully adjust the model parameters, Newtonian and non-Newtonian heat transfer cannot be represented by a single generalized correlation. In addition, the specific heat, thermal conductivity and power-law rheological parameters of CMC solutions were correlated with temperature, over a range compatible with a continuous pasteurization process.

Procedure optimization of silicate rocks dissolution in open vessels for ICP-AES analysis.

The main variables found on procedure of the dissolution silicate rocks using acid dissolution in teflon open vessel for analysis of micro elements by ICP-AES has been determined. The results obtained for some samples showed strong dependence of the rock mineralogical composition, then it was recommended an alkaline fusion step after acid dissolution. The decomposition procedure use 20 mi of an acid mixture of HF:HNO3 in the proportion 3:1 for a fraction of 250 mg pulverized sample. The recommended temperatures were 60 degrees C for attack and 90 degrees C for acid volatilization. The fusion step with 50 mg LiBO2 at 1000 degrees C may be used if non-attacked residue is observed in the solution. The whole time was 6 h per sample. Nine types os silicate rocks that show mineralogical and chemical different compositions were chosen for obtaining the optimization of the variables. The elements used were Ce, Y, Yb and Zr. In addition, ultrassonic nebulization has been used. The percentual standard deviations obtained for five determinations were 0.7 and 1.4 for triplicate samples. The mineralogical and textural information from the petrographical analysis of the samples indicated the need of increasing the fusion step on the optimized procedure.

Evolutionary modeling of larval dispersal in blowflies using non-uniform cellular automata

When the food supply flnishes, or when the larvae of blowflies complete their development and migrate prior to the total removal of the larval substrate, they disperse to find adequate places for pupation, a process known as post-feeding larval dispersal. Based on experimental data of the Initial and final configuration of the dispersion, the reproduction of such spatio-temporal behavior is achieved here by means of the evolutionary search for cellular automata with a distinct transition rule associated with each cell, also known as a nonuniform cellular automata, and with two states per cell in the lattice. Two-dimensional regular lattices and multivalued states will be considered and a practical question is the necessity of discovering a proper set of transition rules. Given that the number of rules is related to the number of cells in the lattice, the search space is very large and an evolution strategy is then considered to optimize the parameters of the transition rules, with two transition rules per cell. As the parameters to be optimized admit a physical interpretation, the obtained computational model can be analyzed to raise some hypothetical explanation of the observed spatiotemporal behavior. © 2006 IEEE.

RAPD optimization for genetic studies with Citrulus lanatus and Sesamum indicum genotypes

The Random Amplified Polymorphic DNA (RAPD) technique is powerful for DNA polymorphism determinations and is widely used in research involving different organisms, but it is known that RAPD can be affected by many factors that may result in false positive bands and non-reproducible assays. In this study, we analyzed the effect of several factors such as DNA template, primer and Taq DNA polymerase concentrations to optimize and standardize the RAPD technique for further genetic studies with Citrulus lanattus and Sesamum indicum L. The best combination of DNA, Taq DNA polymerase enzyme and primer concentrations in RAPD amplification procedures for sesame and watermelon genotypes was established.

Modelación para ajuste de la curva de lactación usando función lineal, no lineal y polinomios segmentados en ganados con alto grado de sangre Brown Swiss

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimization of satellite constellations in the moon

Nowadays, we return to live a period of lunar exploration. China, Japan and India heavily invest in missions to the moon, and then try to implement manned bases on this satellite. These bases must be installed in polar regions due to the apparent existence of water. Therefore, the study of the feasibility of satellite constellations for navigation, control and communication recovers importance. The Moon's gravitational potential and resonant movements due to the proximity to Earth as the Kozai-Lidov resonance, must be considered in addition to other perturbations of lesser magnitude. The usual satellite constellations provide, as a basic feature, continuous and global coverage of the Earth. With this goal, they are designed for the smallest number of objects possible to perform a specific task and this amount is directly related to the altitude of the orbits and visual abilities of the members of the constellation. However the problem is different when the area to be covered is reduced to a given zone. The required number of space objects can be reduced. Furthermore, depending on the mission requirements it may be not necessary to provide continuous coverage. Taking into account the possibility of setting up a constellation that covers a specific region of the Moon on a non-continuous base, in this study we seek a criterion of optimization related to the time between visits. The propagation of the orbits of objects in the constellation in conjunction with the coverage constraints, provide information on the periods of time in which points of the surface are covered by a satellite, and time intervals in which they are not. So we minimize the time between visits considering several sets of possible constellations and using genetic algorithms.

What is the importance of selecting features for non-technical losses identification?

Although non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention in this context. In this paper, we focus on this problem applying a novel feature selection algorithm based on Particle Swarm Optimization and Optimum-Path Forest. The results demonstrated that this method can improve the classification accuracy of possible frauds up to 49% in some datasets composed by industrial and commercial profiles. © 2011 IEEE.