Checking date: 13/05/2022


Course: 2022/2023

Methods and optimization techniques
(16169)
Study: Master in Industrial Mechanical (265)
EPI


Coordinating teacher: MUÑOZ ABELLA, MARIA BELEN

Department assigned to the subject: Department of Mechanical Engineering

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
It is recommended to be engineer in industrial and production field
Objectives
Upon successful completion of this subject, students will be able to: 1. identify and pose an optimization problem. 2. Apply local optimisation methods to solve an optimization problem. 3. Apply genetic algorithms to solve an optimization problem. 4. Apply neural networks to solve an optimization problem.
Skills and learning outcomes
Description of contents: programme
1. Introduction to optimization in mechanical engineering 2. Local optimization methods 3. Global optimization methods. Genetic Algorithms 4. Other optimization techniques. Neural Networks
Learning activities and methodology
Training activities include: - Master classes - Question-answering classes - Student presentations - Individual tutorials - Personal work of the student
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Calendar of Continuous assessment
Basic Bibliography
  • Arora. Introduction to optimum design. Elsevier.
  • Goldberg, D.. Genetic algorithms in search, optimization and machine learning. Addison-Wesley.
  • Haykin,S.. Neural Networks. A comprehensive foundation. Prentice Hall.

The course syllabus may change due academic events or other reasons.