Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

Overview of Caste Differentiation in the Polistinae, Emphasizing the Neotropical Swarm-Founding Polistinae (Hymenoptera, Vespidae, Epiponini)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Synthesis and optimization of colloidal silica nanoparticles and their functionalization with methacrylic acid

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

Evolution of caste in neotropical swarm-founding wasps (Hymenoptera : Vespidae; Epiponini)

Reproductive castes are compared in species of swarming wasps representing all currently recognized genera of Epiponini (Polistinae). New morphometric data for nine measures of body parts and ovarian data are presented for 13 species. These are integrated with all similarly conducted available studies, giving a total of 30 species. Analysis reveals several syndromes relating reproductive and nonreproductive individuals: no meaningful distinction, physiological differences only, reproductives larger than nonreproductives with intermediate individuals present, reproductives different in shape from nonreproductives with no intermediates, and reproductives smaller in some aspects than nonreproductives. Distribution of these syndromes among species is consistent with phylogenetic relationships derived from other data. Optimizing these syndromes on the cladogram indicates that the basal condition of Epiponini is a casteless society that is not comparable to the primitively social genus Polistes where dominant queens control reproduction. Castes originate several times in Epiponini, with different results in different lineages. The best documented evolutionary sequence passes from casteless societies, to those with reproductives larger, to those with reproductives differing in shape from nonreproductives, to those with reproductives smaller in some measures. This sequence is consistent with Wheeler's theory of the origin of caste through developmental switches, and represents the most thorough test of that theory to date.

An evolutionary algorithm for the one-dimensional cutting stock problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analytical optimization of spread and change of exponential decay of generalized Wannier functions in one dimension

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Optimization of neutral hydrolysis reaction of post-consumer PET for chemical recycling

The neutral hydrolysis reaction of post-consumer poly(ethylene terephthalate) in solid state was studied through the reaction of the polymer with water at the molar ratio 1:91 with autogenous pressure. Two sizes of post-consumer PET flakes and temperatures of 135 °C, 170°C and 205°C with pressures of 4.0 atm, 7.5 atm and 13.5 atm, respectively, were considered. With reaction time equal to 6h, the method reached 99% depolymerization at 205°C, 8.2% at 170 °C and 1.7% at 135°C. The reaction extension was measured by separating the terephthalic acid formed in the process and calculating by gravimetry how much material could still be reacted. Through the viscosimetry of diluted, solutions and the counting of carboxylic end groups in the remaining material from the gravimetric assay, it was possible to suggest that the reaction occurs randomly and in the whole volume of the polymeric particle and not solely on the surface. The terephthalic acid obtained and then purified was characterized by elemental analysis, magnetic nuclear resonance, size and panicle size distribution and spectrophotometry in the visible spectrum, and it was similar to the petrochemical equivalent, with purity recorded in carbon base equal to 99.9%.

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.

Multiarea optimal power flow using multiobjective evolutionary algorithm

In this work the multiarea optimal power flow (OPF) problem is decoupled into areas creating a set of regional OPF subproblems. The objective is to solve the optimal dispatch of active and reactive power for a determined area, without interfering in the neighboring areas. The regional OPF subproblems are modeled as a large-scale nonlinear constrained optimization problem, with both continuous and discrete variables. Constraints violated are handled as objective functions of the problem. In this way the original problem is converted to a multiobjective optimization problem, and a specifically-designed multiobjective evolutionary algorithm is proposed for solving the regional OPF subproblems. The proposed approach has been examined and tested on the RTS-96 and IEEE 354-bus test systems. Good quality suboptimal solutions were obtained, proving the effectiveness and robustness of the proposed approach. ©2009 IEEE.

Optimized dynamic response of parallel operation of two single phase inverters based on evolutionary theory

In this work it is proposed an optimized dynamic response of parallel operation of two single-phase inverters with no control communication. The optimization aims the tuning of the slopes of P-ω and Q-V curves so that the system is stable, damped and minimum settling time. The slopes are tuned using an algorithm based on evolutionary theory. Simulation and experimental results are presented to prove the feasibility of the proposed approach. © 2010 IEEE.

GRASP with evolutionary path-relinking for the capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved.

Optimization of the immobilization of sweet potato amylase using glutaraldehyde-agarose support. Characterization of the immobilized enzyme

A simplified procedure for the preparation of immobilized beta-amylase using non-purified extract from fresh sweet potato tubers is established in this paper, using differently activated agarose supports. Beta-amylase glutaraldehyde derivative was the preparation with best features, presenting improved temperature and pH stability and activity. The possibility of reusing the amylase was also shown, when this immobilized enzyme was fully active for five cycles of use. However, immobilization decreased enzyme activity to around 15%. This seems to be mainly due to diffusion limitations of the starch inside the pores of the biocatalyst particles. A fifteen-fold increase in the Km was noticed, while the decrease of Vmax was only 30% (10.1 U mg-1 protein and 7.03 U mg-1 protein for free and immobilized preparations, respectively). © 2013 Elsevier Ltd.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

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.

Swarm-based descriptor combination and its application for image classification

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