Teaching Multivariate Optimization in Process Systems Engineering Through a Case‐Based Learning Methodology
Year: 2025
Type: article
Abstract: ABSTRACT Process Systems Engineering (PSE) is a pillar of Chemical Engineering. It has undergone a great change during the last decades due to the depletion of natural resources, environmental regulations, and increased global business competitiveness. All this has led to an evolution towards the integration and intensification of processes, which requires solving complex and multivariate decision problems. Process optimization provides a scientifically proven methodology for finding the best alternatives in making these decisions through mathematical and computational models. This paper describes a set of exercises integrated into a project that aimed to teach basic concepts of multivariable optimization in the real context of the refining and petrochemical industry within a course in PSE in the BSc degree in Chemical Engineering. For this, the proposed cases were solved using MS Excel Solver. The experience was successful since the students were able to learn the concepts and acquire the skills needed to solve the cases successfully, and this was reflected in the grades obtained. Furthermore, the survey results on the activity, employed to get feedback from the students, showed excellent acceptance.
DOI: 10.1002/cae.70109
Authors: Victoria Rigual, Juan Carlos Domínguez, Julián García, Sara Mateo, Pedro Verdía, M. Virginia Alonso, Mercedes Oliet
Institution: Universidad Complutense de Madrid
Language: English
Subfield: Architecture
Field: Engineering
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4416339125
