EAGLE-Covering the training gap in digital skills for european SMEs manpower
Free training
| Partner: Burgos University | ||||||
| Faculty/Department: Escuela Politécnica Superior/Digitalization Department | ||||||
| Course code: | Course title: Application of optimization techniques in products, processes and business resources | |||||
| Format: Combined | ||||||
| Workload: 8 hours (4 presential lecture hours and 4 hours of autonomous work) | ||||||
| Number of ECTS credits awarded / Type of certification: | ||||||
| Course completion requirements: Continuous assessment (20%): Monitoring of students’ work through evaluation questionnaires. Final evaluation (80%): Formulating and solving a proposed optimization problem. | ||||||
| Target audience: Primary: SMEs technicians. Other: students of technical careers, industry technicians, research institutes, etc. | ||||||
| Learning outcomes: Upon the completion of the course, the participant will: To acquire the basics of the use of optimization techniques on different fields of application and how these techniques provide a competitive advantage. To identify different optimization problems in terms of their mathematical formulation, e.g. linear programming (LP), mixed integer linear programming (MILP), non-linear programming (NLP), etc. To know how to use the solver of Excel to solve optimization problems. | ||||||
| Course structure and syllabus: Hours below are shown in brackets as follows (presential/autonomous work) Transversal concepts (0.5h / 0.5h): Why to use optimization. Fields of interest and how to use it to take the best decisions. Core content (1.5h / 0.5h): Introduction to optimization and mathematical programming. Basic concepts. Decision variables, cost function and constraints. How to formulate an optimization problem. Different kind of formulations. Expert content (0.5h / 1h): What is a solver. Different kinds of algorithms to solve optimization problems. Main difficulties. CBL module (1h / 2h): Students will be given a case study, they have to understand the problem: their variables, constraints and cost function, how to formulate it as an optimization problem and finally, solve it using Excel. Guided reflection and feedback (0.5h / 0h): Depending on the results of the continuous assessment, feedback will be given on the basic concepts and feedback on the proposed optimization problem will also be given. | ||||||
| Recommended readings: Estrategias de Modelado, Simulación y Optimización de Procesos Químicos, L. Puigjaner, P. Ollero, C. de Prada, L. Jimenez, Editorial Síntesis, 2006 (Capítulo 8) Optimization, Foundations and Applications, R. E. Miller, J. Wiley, 2000. | ||||||
| Language competence required: Spanish | ||||||
| Evaluation grid: | ||||||
| A | B | C | D | E | FX | |
| 90-100% | 80-89.9% | 70-79.9% | 60-69.9% | 50-59.9% | 0-49.9% | |
| Lecturer(s): Daniel Sarabia | ||||||
More information about the EAGLE Project
This Project has received funding from the European Union’s Digital Europe Programme (DIGITAL) under the identifier No 101100660.
The views and opinions expressed in the project are solely those of the author(s) and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
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