other · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2023
Optimal process design with simulation-based optimization
Grasso, Giulia
Cited by 0Open access
Abstract
Nowadays, it has become crucial to transform company production processes in order to reduce carbon emissions. Therefore, the company LKAB is working to make the production process of iron ore pellets fossil-free. In particular, this thesis project focuses on the pellet induration stage and addresses the mathematical optimization of the process. In particular, the idea is to combine state-of-the-art optimization algorithms with simulation software. This thesis aims to address the problem of multi-objective optimization within the context of simulation-based scenarios, i.e., the aim is to study Simulation-Based Multi-Objective Optimization Problems. The primary focus of this thesis is to thoroughly investigate and compare three different algorithms applied to two distinct problem formulations. By doing so, we aim to gain valuable insights into the suitability of different approaches and evaluate the algorithms' performance in achieving the desired objectives.
Cite this paper
Grasso, G. (2023). Optimal process design with simulation-based optimization. KTH Publication Database DiVA (KTH Royal Institute of Technology).
Grasso, Giulia. “Optimal process design with simulation-based optimization.” KTH Publication Database DiVA (KTH Royal Institute of Technology), 2023.
Grasso, Giulia. 2023. “Optimal process design with simulation-based optimization.” KTH Publication Database DiVA (KTH Royal Institute of Technology).
Grasso, G. (2023) ‘Optimal process design with simulation-based optimization’, KTH Publication Database DiVA (KTH Royal Institute of Technology).
@misc{grasso2023optimal,
title = {{Optimal process design with simulation-based optimization}},
author = {Grasso, Giulia},
journal = {KTH Publication Database DiVA (KTH Royal Institute of Technology)},
year = {2023}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.