Defesa de doutorado do discente Marcelo Ferreira, dia 18/02 as 08:30.

Defesa de doutorado do discente Marcelo Ferreira, dia 18/02 as 08:30.

Title:
A mathematical formulation and heuristic algorithms for minimizing the makespan and energy cost under time-of-use electricity price in an unrelated parallel machine scheduling problem

Abstract:
In many countries, energy pricing varies according to the time-of-use policy. As a general rule, it is financially advantageous for the industries to plan their production considering this policy. This thesis introduces a new bi-objective unrelated parallel machine scheduling problem with sequence-dependent setup times, in which the objectives are to minimize the makespan and the total energy cost under time-of-use electricity price. We introduced a mixed-integer linear programming formulation and applied the weighted sum method to obtain the Pareto front. We also developed multi-objective methods, based on the Multi-objective Variable Neighborhood Search with intensification procedure (named MOVNS2) and Non-dominated Sorting Genetic Algorithm (NSGA-II), to address large instances of the problem since the formulation cannot solve it in an ac- ceptable computational time for decision-making. We compared the performance of the NSGA-II and MOVNS2 algorithm with two multi-objective algorithms of the literature, MOVNS1, and NSGA-I, concerning the hypervolume and hierarchical cluster counting (HCC) metrics. The results showed that the proposed methods are able to find a good approximation for the Pareto front when compared with the weighted sum method in small instances. Considering large instances, MOVNS2 is superior to MOVNS1, NSGA- I, and NSGA-II regarding the hypervolume metric. Furthermore, NSGA-II outperforms the NSGA-I, MOVNS1, and MOVNS2 multi-objective techniques concerning the HCC metric. Both results are with a 95% confidence level. Thus, the proposed MOVNS2 finds non-dominated solutions with good convergence and NSGA-II with good diversity.

Banca: Prof. Dr. Jose Elias Claudio Arroyo (UFV), Prof. Dr. Lucas de Souza Batista (UFMG), Prof. Dr. Igor Machado Coelho (UFF), Prof. Dr. Puca Huachi Vaz Penna (UFOP), Prof. Dr. Marcone Jamilson Freitas Souza (UFOP - orientador), Prof. Dr. Luciano Perdigão Cota (ITV - coorientador)
Suplentes: Profa. Dra. Luciana Pereira Assis (UFVJM), Prof. Dr. Gustavo Pessin (ITV)
Data: 18/02/2022
Hora: 08h30
Link: meet.google.com/ame-movs-dwp