Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Lipase production by Botryosphaeria ribis EC-01 on soybean and castorbean meals: Optimization, immobilization, and application for biodiesel production

The effects of soybean and castorbean meals were evaluated separately, and in combinations at different ratios, as substrates for lipase production by Botryosphaeria ribis EC-01 in submerged fermentation using only distilled water. The addition of glycerol analytical grade (AG) and glycerol crude (CG) to soybean and castorbean meals separately and in combination, were also examined for lipase production. Glycerol-AG increased enzyme production, whereas glycerol-CG decreased it. A 24 factorial design was developed to determine the best concentrations of soybean meal, castorbean meal, glycerol-AG, and KH2PO4 to optimize lipase production by B. ribis EC-01. Soybean meal and glycerol-AG had a significant effect on lipase production, whereas castorbean meal did not. A second treatment (22 factorial design central composite) was developed, and optimal lipase production (4,820 U/g of dry solids content (ds)) was obtained when B. ribis EC-01 was grown on 0.5 % (w/v) soybean meal and 5.2 % (v/v) glycerol in distilled water, which was in agreement with the predicted value (4,892 U/g ds) calculated by the model. The unitary cost of lipase production determined under the optimized conditions developed ranged from US$0.42 to 0.44 based on nutrient costs. The fungal lipase was immobilized onto Celite and showed high thermal stability and was used for transesterification of soybean oil in methanol (1:3) resulting in 36 % of fatty acyl alkyl ester content. The apparent K m and V max were determined and were 1.86 mM and 14.29 μmol min -1 mg-1, respectively. © 2013 Springer Science+Business Media New York.

Comparative analysis of strut-and-tie models using Smooth Evolutionary Structural Optimization

The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.

Optimization of economic benefits from fishery and forestry in Bío-Bío, Chile

Includes bibliography

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%).

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.

Thermochemical equilibrium modeling of a biomass downdraft gasifier: Constrained and unconstrained non-stoichiometric models

The objective of this work is to develop a non-stoichiometric equilibrium model to study parameter effects in the gasification process of a feedstock in downdraft gasifiers. The non-stoichiometric equilibrium model is also known as the Gibbs free energy minimization method. Four models were developed and tested. First a pure non-stoichiometric equilibrium model called M1 was developed; then the methane content was constrained by correlating experimental data and generating the model M2. A kinetic constraint that determines the apparent gasification rate was considered for model M3 and finally the two aforementioned constraints were implemented together in model M4. Models M2 and M4 showed to be the more accurate among the four developed models with mean RMS (root mean square error) values of 1.25 each.Also the gasification of Brazilian Pinus elliottii in a downdraft gasifier with air as gasification agent was studied. The input parameters considered were: (a) equivalence ratio (0.28-035); (b) moisture content (5-20%); (c) gasification time (30-120 min) and carbon conversion efficiency (80-100%). (C) 2014 Elsevier Ltd. 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.

Characterization and optimization of levan production by Bacillus subtilis NATTO

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Social-spider optimization-based artificial neural networks training and its applications for Parkinson's disease identification

Evolutionary algorithms have been widely used for Artificial Neural Networks (ANN) training, being the idea to update the neurons' weights using social dynamics of living organisms in order to decrease the classification error. In this paper, we have introduced Social-Spider Optimization to improve the training phase of ANN with Multilayer perceptrons, and we validated the proposed approach in the context of Parkinson's Disease recognition. The experimental section has been carried out against with five other well-known meta-heuristics techniques, and it has shown SSO can be a suitable approach for ANN-MLP training step.

Production of β-(1,3)-glucanases by Trichoderma harzianum Rifai: Optimization and Application to Produce Gluco-oligosaccharides from Paramylon and Pustulan

β-(1→3)-Glucanases were produced by Trichoderma harzianum Rifai PAMB-86 cultivated on botryosphaeran in a bench-fermenter and optimised by the response surface method. Maximal enzyme titres occurred at 5 days, initial pH 5.5 and aeration of 1.5vvm. β-(1→3)-The β-glucanolytic enzyme complex produced by T. harzianum Rifai PAMB- 86 was fractionated by gel filtration into 2 fractions (F-I, F-II), and employed to produce gluco-oligosaccharides from algal paramylon ((1→3)-β-D-glucan) and lichen pustulan ((1→6)-β-D-glucan). Both enzymes attacked paramylon to the extent of ~15-20% in 30 min releasing glucose and laminaribiose as major end-products, and laminarioligosaccharides of degree of polymerization (DP) ≥3. Only F-I degraded pustulan resulting in ~2% degradation at 30 min, with glucose, gentiobiose and gentio-oligosaccharides of DP ≥4 as major products. The difference in the nature of the hydrolysis products can be explained by the substrate specificities of each enzyme fraction, and the structural differences of the β-D-glucans attacked.

Saddle Point and Second Order Optimality in Nondifferentiable Nonlinear Abstract Multiobjective Optimization

This article deals with a vector optimization problem with cone constraints in a Banach space setting. By making use of a real-valued Lagrangian and the concept of generalized subconvex-like functions, weakly efficient solutions are characterized through saddle point type conditions. The results, jointly with the notion of generalized Hessian (introduced in [Cominetti, R., Correa, R.: A generalized second-order derivative in nonsmooth optimization. SIAM J. Control Optim. 28, 789–809 (1990)]), are applied to achieve second order necessary and sufficient optimality conditions (without requiring twice differentiability for the objective and constraining functions) for the particular case when the functionals involved are defined on a general Banach space into finite dimensional ones.

Construction of pediatric homogeneous phantoms for optimization of chest and skull radiographs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)