Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

Análise da magnetohidrodinâmica com transferência de calor em canais de placas paralelas via transformação integral

The main goal of the present work is related to the dynamics of the steady state, incompressible, laminar flow with heat transfer, of an electrically conducting and Newtonian fluid inside a flat parallel-plate channel under the action of an external and uniform magnetic field. For solution of the governing equations, written in the parabolic boundary layer and stream-function formulation, it was employed the hybrid, numericalanalytical, approach known as Generalized Integral Transform Technique (GITT). The flow is sustained by a pressure gradient and the magnetic field is applied in the direction normal to the flow and is assumed that normal magnetic field is kept uniform, remaining larger than any other fields generated in other directions. In order to evaluate the influence of the applied magnetic field on both entrance regions, thermal and hydrodynamic, for this forced convection problem, as well as for validating purposes of the adopted solution methodology, two kinds of channel entry conditions for the velocity field were used: an uniform and an non-MHD parabolic profile. On the other hand, for the thermal problem only an uniform temperature profile at the channel inlet was employed as boundary condition. Along the channel wall, plates are maintained at constant temperature, either equal to or different from each other. Results for the velocity and temperature fields as well as for the main related potentials are produced and compared, for validation purposes, to results reported on literature as function of the main dimensionless governing parameters as Reynolds and Hartman numbers, for typical situations. Finally, in order to illustrate the consistency of the integral transform method, convergence analyses are also effectuated and presented

Aplicações da q-Álgebra em física da matéria condensada

We address the generalization of thermodynamic quantity q-deformed by q-algebra that describes a general algebra for bosons and fermions . The motivation for our study stems from an interest to strengthen our initial ideas, and a possible experimental application. On our journey, we met a generalization of the recently proposed formalism of the q-calculus, which is the application of a generalized sequence described by two parameters deformation positive real independent and q1 and q2, known for Fibonacci oscillators . We apply the wellknown problem of Landau diamagnetism immersed in a space D-dimensional, which still generates good discussions by its nature, and dependence with the number of dimensions D, enables us future extend its application to systems extra-dimensional, such as Modern Cosmology, Particle Physics and String Theory. We compare our results with some experimentally obtained performing major equity. We also use the formalism of the oscillators to Einstein and Debye solid, strengthening the interpretation of the q-deformation acting as a factor of disturbance or impurity in a given system, modifying the properties of the same. Our results show that the insertion of two parameters of disorder, allowed a wider range of adjustment , i.e., enabling change only the desired property, e.g., the thermal conductivity of a same element without the waste essence