Research Projects

Combinatorial Optimization - Exact methods, Heuristics and Meta-Heuristics

Development of approaches to large-scale problems in combinatorial optimization, as well as the adaptation and application of existing methods to problems applied in different sectors of the industry.

Publications:

  • Simões, Emiliana Mara Lopes, Lucas De Souza Batista, and Marcone Jamilson Freitas Souza. “A Matheuristic Algorithm for the Multiple-Depot Vehicle and Crew Scheduling Problem.” IEEE Access 9 (2021): 155897-155923.
  • Maravilha, André L., Eduardo G. Carrano, and Felipe Campelo. “A recombination‐based matheuristic for mixed integer programming problems with binary variables.” International Transactions in Operational Research 27.1 (2020): 418-434.

Computational Intelligence Applied to the Financial Sector

Development and application of computational intelligence tools for modeling and predicting series and events related to the financial sector.

Publications:

  • de Arruda Pereira, Marconi, et al. “A comparative study of optimization models in genetic programming-based rule extraction problems.” Soft Computing 23.4 (2019): 1179-1197
  • Assis, Carlos AS, et al. “Hybrid deep learning approach for financial time series classification.” Revista Brasileira de Computação Aplicada 10.2 (2018): 54-63.
  • de Assis, Carlos Alberto Silva, Eduardo Gontijo Carrano, and Adriano Cesar Machado Pereira. “Predição de tendências em séries financeiras utilizando metaclassificadores.” Economia Aplicada 24.1 (2020): 29-78.

Game Theory and Multicriteria Decision Making

Development and integration of multicriteria decision-making tools for solving engineering problems.

Publications:

  • Campolina, Paulo Azevedo Meijon, and Lucas S. Batista. “Uma estratégia automatizada de day-trade por meio de comitê de indicadores técnicos.” XIV Congresso Brasileiro de Inteligência Computacional 1.1 (2019).
  • Campolina, Paulo Azevedo Meijon, and Lucas S. Batista. “Estratégia Automatizada de Decisão Multicritério no Mercado Financeiro”. *XIV Conferência Brasileira de Dinâmica, Controle e Aplicações 1.1 (2019).

Microwave Imaging

Microwave Imaging is an emerging field with many applications in biomedical engineering, through-the-wall imaging, geoscience, among others. The imaging problem is an instance of the electromagnetic inverse scattering problem, where the media is recovered by means of measurements of the scattered around the domain of interest. This is an ill-posed, nonlinear, and multimodal problem. Our goal is to improve the algorithms and methods for measuring the performance of the reconstructions. We have also designed a library for algorithm development and performance experimentation.

Publications:

  • Batista, André Costa, Ricardo Adriano, and Lucas S. Batista. “EISPY2D: An Open-Source Python Library for the Development and Comparison of Algorithms in Two-Dimensional Electromagnetic Inverse Scattering Problems.” arXiv preprint arXiv:2111.02185 (2021).
  • Batista, André Costa, Lucas S. Batista, and Ricardo Adriano. “A Quadratic Programming Approach for Microwave Imaging.” IEEE Transactions on Antennas and Propagation (2021).

Modular Approaches to Optimization

Development of modular descriptions and approaches for optimization algorithms, to enable a component-based analysis of the behavior of algorithms, as well as the accelerated development of new algorithmic variants and the reproducibility of methods published in the literature.

Publications:

  • Campelo, F., L. S. Batista, and C. Aranha. “The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition”. Journal of Statistical Software, vol. 92, no. 6, Feb. 2020, pp. 1-39.

Multi-Objective Optimization

Development of algorithms for solving multi-objective optimization problems with specificities such as: variable uncertainties, high number of objectives, arbitrary non-linear constraints, and presence of decision maker preferences.

Publications:

  • Gomes, Ana Cristina Lima, Martín Gómez Ravetti, and Eduardo G. Carrano. “Multi-objective matheuristic for minimization of total tardiness and energy costs in a steel industry heat treatment line.” Computers & Industrial Engineering 151 (2021): 106929.
  • Valadão, Mônica AC, and Lucas S. Batista. “A comparative study on surrogate models for SAEAs.” Optimization Letters 14 (2020): 2595-2614.

Network Optimization

Development and application of algorithms for optimizing data networks, electrical networks, and other engineering applications.

Publications:

  • Araujo, Jean NR, Lucas S. Batista, and Claudio C. Monteiro. “Improving proactive routing with a multicriteria and adaptive framework in ad-hoc wireless networks.” Wireless Networks 26.6 (2020): 4595-4614.
  • Araujo, Jean Nunes R., Claudio de Castro Monteiro, and Lucas de Souza Batista. “Multicriteria QoS-aware Solution in Wireless Multi-hop Networks.” ICWMC 2017 (2017): 25.

Optimization Applied to the Electricity Sector

Development of integrated optimization tools for solving problems in the electricity sector, such as: planning the robust expansion of electricity networks, asset management in the electricity sector, failure management (restoration, reconfiguration, routing of maintenance teams), among others.

Publications:

  • Goulart, Fillipe, et al. “Permutation-based optimization for the load restoration problem with improved time estimation of maneuvers.” International Journal of Electrical Power & Energy Systems 101 (2018): 339-355.
  • Campelo, Felipe, et al. “Multicriteria transformer asset management with maintenance and planning perspectives.” IET Generation, Transmission & Distribution 10.9 (2016): 2087-2097.
  • Costa, Mateus H., et al. “Minimizing undesirable load shedding through robust coordination of directional overcurrent relays.” International Journal of Electrical Power & Energy Systems 113 (2019): 748-757.
  • Maravilha, André L., et al. “Scheduling maneuvers for the restoration of electric power distribution networks: Formulation and heuristics.” Electric Power Systems Research 163 (2018): 301-309.

Statistical Modeling Applied to Engineering

Development, adaptation and application of statistical modeling techniques to engineering problems.

Publications:

  • Bessani, Michel, and Diego A. da Mata. “Exploratory Factor Analysis of Distribution Networks Characterization by Metrics of Complex Networks Theory.” Simpósio Brasileiro de Sistemas Elétricos-SBSE 1.1 (2020).
  • da Mata, Diego A., and Michel Bessani. “Restabelecimento de Sistemas de Distribuição-Abordagem Hibrida de Algoritmo Genético e Busca local.” Simpósio Brasileiro de Sistemas Elétricos-SBSE 1.1 (2020).

Statistical Protocols for Experimental Research on Algorithms

Development of statistical protocols for experimental evaluation and comparison of algorithms, including sample size calculation, best/worst case comparison, and evaluation of convergence characteristics in the presence of censored observations.

Publications:

  • Campelo, Felipe, and Elizabeth F. Wanner. “Sample size calculations for the experimental comparison of multiple algorithms on multiple problem instances.” Journal of Heuristics 26.6 (2020): 851-883.
  • Campelo, Felipe, and Fernanda Takahashi. “Sample size estimation for power and accuracy in the experimental comparison of algorithms.” Journal of Heuristics 25.2 (2019): 305-338.