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Design Optimization, 6 credits
Konstruktionsoptimering, 6 hp
TMKT48
Main field of study
Mechanical EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Johan ÖlvanderDirector of studies or equivalent
Peter HallbergEducation components
Preliminary scheduled hours: 70 hRecommended self-study hours: 90 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Mechanical EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Design and Product Development
- Industrial Engineering and Management - International, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Mechanical Engineering, M Sc in Engineering
- Mechanical Engineering, Master's programme
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Introductory courses in mathematics, mechanics, solid mechanics and mechanical engineering design.Intended learning outcomes
The course aims at integrating traditional design methodologies with concepts and techniques of modern optimisation theory and practice. In the course the student will learn to create an appropriate mathematical description (a simulation model) of the design problem, to formulate the optimisation problem and finally to use numerical optimisation techniques and computer support tools in order to solve the problem. After the course the student:
- Should understand and be able to describe the function of a set of iterative optimization methods such as Genetic Algorithms, the Complex Method, and gradient methods (Newton methods)
- Should be able to compare and evaluate the suitability of different optimization methods for different problem types.
- Should be able to formulate design problems as mathematical optimization problems.
- Should be able to implement mathematical models of design problems in MATLAB and solve them using numerical optimization methods.
- Should be able to describe how simulation and optimization could be connected.
- Should be able to implement the connection between simulation and optimization in the MATLAB/Simulink environment.
- Should be able to analyze the sensitivity of the obtain optimal solutions.
- Should be able to discuss the plausibility of the results.
Course content
Optimization in the desing process
Optimization methods: Genetic Algorithms, the Complex method, gradient based methods
Formulation of design problems as optimization problems
Formulation of objective functions
Optimization based on simulation models
Multi-objective optimization
Constraints and penalty functions
Post optimal analysis
Sensitivity analysis
Teaching and working methods
Lectures, seminars, computer exercises where the methods and techniques thought in the course are applied to real design tasks.
Examination
| UPG1 | Design task | 1 credits | U, G |
| DAT1 | Written examination | 5 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för ekonomisk och industriell utvecklingDirector of Studies or equivalent
Peter HallbergExaminer
Johan ÖlvanderCourse website and other links
Education components
Preliminary scheduled hours: 70 hRecommended self-study hours: 90 h
Course literature
Kompendium och vetenskapliga artiklar.| Code | Name | Scope | Grading scale |
|---|---|---|---|
| UPG1 | Design task | 1 credits | U, G |
| DAT1 | Written examination | 5 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
Kompendium och vetenskapliga artiklar.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
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X
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X
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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X
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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| 2.2 Experimentation, investigation, and knowledge discovery |
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X
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| 2.3 System thinking |
X
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| 2.4 Attitudes, thought, and learning |
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X
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| 2.5 Ethics, equity, and other responsibilities |
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X
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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| 3.2 Communications |
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| 3.3 Communication in foreign languages |
X
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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| 4.5 Implementing |
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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