Geraldo R. Mateus

About Geraldo R. Mateus

Geraldo R. Mateus, With an exceptional h-index of 38 and a recent h-index of 18 (since 2020), a distinguished researcher at Universidade Federal de Minas Gerais,

His recent articles reflect a diverse array of research interests and contributions to the field:

Minimizing Carbon Emission in Hybrid Flow Shop Scheduling: A Comparative Analysis of Flow-based and Set Partitioning Formulations

MIP-Heuristics for the Capacitated Lot-Sizing with Hybrid Flow Shop Integration

cudaBRKGA-CNN: An Approach for Optimizing Convolutional Neural Network Architectures

Modeling and Analysis of Different Reconfiguration Strategies for Virtual Network Function Placement and Chaining with Service Classes Identification

A Hybrid Flow Shop Scheduling: A Comparative Analysis of Minimizing Carbon Emission and Minimizing the Total Completion Time

A demand aware strategy for a machine learning approach to vnf-pc problem

A hybrid heuristic for capacitated three-level lot-sizing and replenishment problems with a distribution structure

A mixed-integer programming formulation and heuristics for an integrated production planning and scheduling problem

Geraldo R. Mateus Information

University

Position

Professor de Ciência da Computação

Citations(all)

4098

Citations(since 2020)

1106

Cited By

3734

hIndex(all)

38

hIndex(since 2020)

18

i10Index(all)

81

i10Index(since 2020)

25

Email

University Profile Page

Google Scholar

Top articles of Geraldo R. Mateus

Minimizing Carbon Emission in Hybrid Flow Shop Scheduling: A Comparative Analysis of Flow-based and Set Partitioning Formulations

Procedia Computer Science

2024/1/1

MIP-Heuristics for the Capacitated Lot-Sizing with Hybrid Flow Shop Integration

2023/8/6

cudaBRKGA-CNN: An Approach for Optimizing Convolutional Neural Network Architectures

2023/7/1

Modeling and Analysis of Different Reconfiguration Strategies for Virtual Network Function Placement and Chaining with Service Classes Identification

IEEE Latin America Transactions

2023/3/14

A Hybrid Flow Shop Scheduling: A Comparative Analysis of Minimizing Carbon Emission and Minimizing the Total Completion Time

2023

A demand aware strategy for a machine learning approach to vnf-pc problem

2022/11/7

A hybrid heuristic for capacitated three-level lot-sizing and replenishment problems with a distribution structure

Computers & Industrial Engineering

2022/11/1

A mixed-integer programming formulation and heuristics for an integrated production planning and scheduling problem

2022/7/11

Valid inequalities and branch-and-cut algorithm for the pickup and delivery traveling salesman problem with multiple stacks

European Journal of Operational Research

2022/7/1

Branch‐and‐cut algorithms for the‐arborescence star problem

International Transactions in Operational Research

2022/7

Multi-echelon supply chains with uncertain seasonal demands and lead times using deep reinforcement learning

arXiv preprint arXiv:2201.04651

2022/1/12

A hybrid optimization-Machine Learning approach for the VNF placement and chaining problem

Computer Networks

2021/11/9

Uma Abordagem Heurística para o Posicionamento e Encadeamento de Funções Virtuais de Rede em Ambientes Online

2021/8/16

Applying and comparing policy gradient methods to multi-echelon supply chains with uncertain demands and lead times

2021/6/20

Coupling Feasibility Pump and Large Neighborhood Search to solve the Steiner team orienteering problem

Computers & Operations Research

2021/4/1

Operations research at bulk terminal: a parallel column generation approach

Heuristics for Optimization and Learning

2021

On the analysis of online and periodic virtual network embedding in multi-domain environments

International Journal of Networking and Virtual Organisations

2021

Alocação de Recursos para Redes Virtuais com Seleção de Método de Resolução via Aprendizado de Máquina

2020/12/7

Deep reinforcement learning and optimization approach for multi-echelon supply chain with uncertain demands

2020/9/22

Corrigendum to “A cutting-plane algorithm for the Steiner team orienteering problem”[Comput. Ind. Eng. 135 (2019) 922–939]

2020/3

See List of Professors in Geraldo R. Mateus University(Universidade Federal de Minas Gerais)