Green-Markov models - new optimization strategies: a case study for user allocation in co-channel macro/femto networks

ABSTRACT: The femtocell concept aims to combine fixed-line broadband access with mobile telephony using the deployment of low-cost, low-power third and fourth generation base stations in the subscribers' homes. While the self-configuration of femtocells is a plus, it can limit the quality of service (QoS) for the users and reduce the efficiency of the network, based on outdated allocation parameters such as signal power level. To this end, this paper presents a proposal for optimized allocation of users on a co-channel macro-femto network, that enable self-configuration and public access, aiming to maximize the quality of service of applications and using more efficiently the available energy, seeking the concept of Green networking. Thus, when the user needs to connect to make a voice or a data call, the mobile phone has to decide which network to connect, using the information of number of connections, the QoS parameters (packet loss and throughput) and the signal power level of each network. For this purpose, the system is modeled as a Markov Decision Process, which is formulated to obtain an optimal policy that can be applied on the mobile phone. The policy created is flexible, allowing different analyzes, and adaptive to the specific characteristics defined by the telephone company. The results show that compared to traditional QoS approaches, the policy proposed here can improve energy efficiency by up to 10%.

FBG optimization using spline encoded evolution strategy

ABSTRACT: This paper presents an encoding scheme adapted for Fiber Bragg Grating (FBG) optimization using metaheuristics. The proposed encoding scheme uses spline approximations in order to build softened refractive index profiles from few encoded parameters. This approach is suitable for Fiber Bragg Grating (FBG) synthesis because it ensures both the reduction of the problem dimensionality and the respect of important restrictions associated to the FBG manufacture. Simulations are shown where an ES using the spline encoding was able to converge faster and produce more interesting filters, when compared with conventional encoding schemes.

Optimization of annatto (Bixa orellana L.) drying in fixed bed

ABSTRACT: The drying of annatto seeds (Bixa orellana L.), red piave cultivate, was studied in a fixed bed dryer. The best conditions were estimated to minimize the loss of coloring and to obtain final moisture of the seeds in appropriate levels to its conservation and maintenance of quality. The quantification of the influence of entrance variables in the final contents of bixin and moisture seeds and the identification of the optimal point was performed through the techniques of factorial design, response surfaces methodology, canonical analysis and desirability function. It was verified that the final moisture of the seeds may be estimated by a second-order polynomial model and that the final content of bixin is only significantly influenced by the time of drying being described properly by a linear model, for the seeds used in this study.

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

Crop optimization and pre-steps standardization to get a Bipolaris euphorbiae-based bioherbicide

Making bioproducts available to the market requires finding appropriate processes for mass production and formulation of biological agents. This study aimed at evaluating the Bipolaris euphorbiae production in a solid medium (fermentation in solid substrate) and in a biphasic system (growth in a liquid medium followed by growth in a solid medium), as well as determining the processes for collecting and drying conidia, under laboratory conditions. The influence of the incubation period and inoculum quantity were also investigated. The conidia were dried by using an oven (30ºC, 35ºC, 40ºC, 45ºC, 50ºC, 55ºC and 60ºC), and laminar flow, continuous air flow and aseptic chamber at room temperature. Dry conidia were obtained by sieving and grinding in a ball mill, hammer mill or grain grinder. The conidia viability and sporulation efficiency were evaluated in the solid medium and in the biphasic system. For growth period, the best sporulation on solid medium was obtained after 10 days of incubation, reaching 8.3 x 10(7) conidia g-1 of substrate. The biphasic system did not increase the B. euphorbiae sporulation (4.5 x 10(7) conidia g-1 of substrate), after 14 days, and the amount of liquid inoculum used in this system was not an important factor for increasing its production. The continuous air flow and laminar flow preserved the conidial viability (94.6% and 99.1%, respectively), while promoting a great moisture loss (62.6% and 54.0%, respectively). All the grinding processes reduced the conidia germination (86.2%, 10.5% and 12%, respectively), while sieving allowed the collecting of powdered conidia with high viability (94.8%).

Particle swarm optimization aplicada ao planejamento da expansão de sistemas de transmissão

Pós-graduação em Engenharia Elétrica - FEIS

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

Thermoplastic polyesters and Co-polyesters derived from vegetable oil: synthesis and optimization of melt polycondensation for medium and long chain poly(omega-hydroxyfatty acid)s and their ester derivatives

The synthesis of a series of omega-hydroxyfatty acid (omega-OHFA) monomers and their methyl ester derivatives (Me-omega-OHFA) from mono-unsaturated fatty acids and alcohols via ozonolysis-reduction/crossmetathesis reactions is described. Melt polycondensation of the monomers yielded thermoplastic poly(omega-hydroxyfatty acid)s [-(CH2)(n)-COO-](x) with medium (n = 8 and 12) and long (n = 17) repeating monomer units. The omega-OHFAs and Me-omega-OHFAs were all obtained in good yield (>= 80%) and purity (>= 97%) as established by H-1 NMR, Fourier Transform infra-red spectroscopy (FT-IR), mass spectroscopy (ESI-MS) and high performance liquid chromatography (HPLC) analyses. The average molecular size (M-n) and distribution (PDI) of the poly(omega-hydroxyfatty acid)s (P(omega-OHFA)s) and poly(omega-hydroxyfatty ester) s (P(Me-omega-OHFA) s) as determined by GPC varied with organo-metallic Ti(IV) isopropoxide [Ti(OiPr)(4)] polycondensation catalyst amount, reaction time and temperature. An optimization of the polymerization process provided P(omega-OHFA) s and P(Me-omega-OHFA) s with M-n and PDI values desirable for high end applications. Co-polymerization of the long chain (n = 12) and medium chain (n = 8) Me-omega-OHFAs by melt polycondensation yielded poly(omega-hydroxy tridecanoate/omega-hydroxy nonanoate) random co-polyesters (M-n = 11000- 18500 g mol(-1)) with varying molar compositions.

Chemometric optimization of solid-liquid extraction with low-temperature partition (SLE-LTP) for determination of persistent organic pollutants in Caiman yacare eggs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Characterization and optimization of levan production by Bacillus subtilis NATTO

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimization of Antitrypanosomatid Agents: Identification of Nonmutagenic Drug Candidates with in Vivo Activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discovering promising regions to help global numerical optimization algorithms

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.

A smooth evolutionary structural optimization procedure applied to plane stress problem

Topological optimization problems based on stress criteria are solved using two techniques in this paper. The first technique is the conventional Evolutionary Structural Optimization (ESO), which is known as hard kill, because the material is discretely removed; that is, the elements under low stress that are being inefficiently utilized have their constitutive matrix has suddenly reduced. The second technique, proposed in a previous paper, is a variant of the ESO procedure and is called Smooth ESO (SESO), which is based on the philosophy that if an element is not really necessary for the structure, its contribution to the structural stiffness will gradually diminish until it no longer influences the structure; its removal is thus performed smoothly. This procedure is known as "soft-kill"; that is, not all of the elements removed from the structure using the ESO criterion are discarded. Thus, the elements returned to the structure must provide a good conditioning system that will be resolved in the next iteration, and they are considered important to the optimization process. To evaluate elasticity problems numerically, finite element analysis is applied, but instead of using conventional quadrilateral finite elements, a plane-stress triangular finite element was implemented with high-order modes for solving complex geometric problems. A number of typical examples demonstrate that the proposed approach is effective for solving problems of bi-dimensional elasticity. (C) 2014 Elsevier Ltd. All rights reserved.

The influence of self-weight of elastic 2D structures in topology optimization via numerical technique Smooth Evolutionary Structural Optimization (SESO)

This paper deals with topology optimization in plane elastic-linear problems considering the influence of the self weight in efforts in structural elements. For this purpose it is used a numerical technique called SESO (Smooth ESO), which is based on the procedure for progressive decrease of the inefficient stiffness element contribution at lower stresses until he has no more influence. The SESO is applied with the finite element method and is utilized a triangular finite element and high order. This paper extends the technique SESO for application its self weight where the program, in computing the volume and specific weight, automatically generates a concentrated equivalent force to each node of the element. The evaluation is finalized with the definition of a model of strut-and-tie resulting in regions of stress concentration. Examples are presented with optimum topology structures obtaining optimal settings. (C) 2012 CIMNE (Universitat Politecnica de Catalunya). Published by Elsevier Espana, S.L.U. All rights reserved.