Defesa de Exame de Qualificação – Maurício Pereira Dal Pont – 10/5/2019

17/05/2019 16:39
Defesa de Exame de Qualificação
Aluno Maurício Pereira Dal Pont
Orientador Prof. Julio Elias Normey-Rico, Dr. – DAS/UFSC
Coorientador Prof. Daniel Martins Lima, Dr. – UFSC/Blumenau


10/5/2019  10h00  (sexta-feira)

Sala 002 – PPGEEL



Prof. Jomi Fred Hübner, Dr. – DAS/UFSC (presidente);

Prof. Jorge Otávio Trierweiler,  Dr. – ENQ/UFRGS;

Prof. Alex Sandro Roschild Pinto, Dr. – INE/UFSC;

Prof. João Carlos Ferreira, Dr. – EMC/UFSC.



MPC with Machine Learning Applied to Resource Allocation Problem using Lambda Architecture
Abstract: The resource allocation problem is the process of allocating limited resources for a vast amount of tasks. Within this problem, there are several important variants such as the stochastic time-variant resource allocation problem. This problem is relevant within environments where the distribution of resources varies with time, bringing difficulties to forecasting. Related research generally addresses the problem by using model predictive control (MPC) techniques or machine learning (ML) algorithms. However, both can be applied together in order to improve the tasks prioritization and forecasting. Therefore, this work proposes a solution using the concept of lambda architecture in order to tackle the time-variant and distinct input information. First results show that the integration between MPC and ML prioritizes the resource allocation and a Markov chain model is capable of forecasting tasks, optimizing a strategic binary control. We analyze a case study of a real problem and show how the proposal was built and its advantages over the traditional method.