Luzia Vidal de Souza

Applying correlation to enhance boosting technique using genetic programming as base learner

This paper explores the Genetic Programming and Boosting technique to obtain an ensemble of regressors and proposes a new formula for the updating of weights, as well as for the final hypothesis. Differently from studies found in the literature, in this paper we investigate the use of the correlation metric as an additional factor for the error metric. This new approach, called Boosting using Correlation Coefficients (BCC) has been empirically obtained after trying to improve the results of the other methods. To validate this method, we conducted two groups of experiments. In the first group, we explore the BCC for time series forecasting, in academic series and in a widespread Monte Carlo simulation covering the entire ARMA spectrum. The Genetic Programming (GP) is used as a base learner and the mean squared error (MSE) has been used to compare the accuracy of the proposed method against the results obtained by GP, GP using traditional boosting and the traditional statistical methodology (ARMA). The second group of experiments aims at evaluating the proposed method on multivariate regression problems by choosing Cart (Classification and Regression Tree) as the base learner.

Heuristic methods applied to the optimization school bus transportation routes: a real case

The problem discussed in this paper is similar to the Vehicle Routing Problem (VRP), however new contributions are proposed. In this work a heuristic algorithm is proposed to determine the set of the Bus Stops. A new approach is proposed to construct digital maps containing the roads where the vehicles will be able to travel, since there are no digital maps of these regions. The real distances between the points are calculated and the heuristics Location Based Heuristic with some additional features was used to propose the new routes. The algorithm was named by Adapted Location Based Heuristic (ALBH). The School Transportation Problem was implemented in the State of Parana for 399 cities. We present here the results obtained for 10 of the 399 cities. The results obtained by using this approach showed improvement in daily distance performed and in the amount of the vehicles used to do the job.

Estudo da localização de escolas municipais no município de São Jerônimo da Serra - PR

O objetivo da pesquisa e o de propor e estudar diversos cenarios envolvendo a localizacao das escolas municipais de Sao Jeronimo da Serra, a fim de minimizar as distâncias percorridas pelos estudantes ate suas instituicoes de ensino. Na primeira etapa, realiza-se uma analise da atual localizacao das escolas municipais e dos dados do transporte escolar. Na segunda, sao realizadas simulacoes considerando a localizacao das escolas existentes. Nessa etapa, sao utilizados os algoritmos de Teitz & Bart e Simulated Annealing para resolver o problema de p-medianas. Na terceira etapa, e realizada a alocacao dos estudantes para as escolas mais proximas utilizando o algoritmo de Gillett & Johnson modificado. Na ultima etapa, e aplicado o algoritmo Location Based Heuristic Adaptado para o roteamento do transporte escolar, com a finalidade de comparar os resultados obtidos com a situacao atual do municipio.