Applied Optimization II, 6 credits

Tillämpad optimering II, 6 hp

TNK105

Main field of study

Applied Mathematics Transportation Systems Engineering

Course level

Second cycle

Course type

Programme course

Examiner

Nikolaos Pappas

Director of studies or equivalent

Erik Bergfeldt

Education components

Preliminary scheduled hours: 20 h
Recommended self-study hours: 140 h

Available for exchange students

Yes
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CKTS Communication and Transportation Engineering, M Sc in Engineering 7 (Autumn 2017) 2 3 English Norrköping, Norrköping E
6CKTS Communication and Transportation Engineering, M Sc in Engineering 9 (Autumn 2017) 2 3 English Norrköping, Norrköping E
6MTSL Intelligent Transport Systems and Logistics, Master's programme 3 (Autumn 2017) 2 3 English Norrköping, Norrköping E

Main field of study

Applied Mathematics, Transportation Systems Engineering

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Intelligent Transport Systems and Logistics, Master's programme
  • Communication and Transportation Engineering, M Sc in Engineering

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

Applied optimization I, programming principles, and data structures, or equivalent

Intended learning outcomes

The aim of the course is to provide the participants with insights in applying optimization to solving problems originating from real life applications. The participants will gain knowledge of the process of using optimization theories and methodologies for defining, modeling, solving, and analyzing optimizing problems. After the course, the participants shall be able to

  • connect the course subjects to their study program
  • study and analyze problems in the area of transport and communications from an optimization perspective
  • use a modeling system for large scale optimization
  • use efficient data structures in implementation of optimization algorithms
  • develop, implement, and evaluate problem-specific methods that find solutions by effectively exploiting problem structure
  • verbal and written presentation of results

Course content

  • Problem definition, literature study, and information search
  • Study of to what extent the problem can be solved by mathematical modeling and general optimization software
  • Design of problem-specific methods, in particular heuristics
  • Design of data structures for method implementation
  • Implementation, experimentation, analysis and evaluation of optimization methods

Teaching and working methods

The course consists of seminars and project work with supervision

Examination

UPG1Project work6 creditsU, 3, 4, 5

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för teknik och naturvetenskap

Director of Studies or equivalent

Erik Bergfeldt

Examiner

Nikolaos Pappas

Education components

Preliminary scheduled hours: 20 h
Recommended self-study hours: 140 h

Course literature

Hänvisning till olika litteratur beroende på tilldelat projekt.
Code Name Scope Grading scale
UPG1 Project work 6 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. 

Hänvisning till olika litteratur beroende på tilldelat projekt.

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)
X
UPG1

                            
1.2 Fundamental engineering knowledge (G1X level)
X
UPG1

                            
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
X
UPG1

                            
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)

                            
1.5 Insight into current research and development work

                            
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
2.1 Analytical reasoning and problem solving
X
UPG1

                            
2.2 Experimentation, investigation, and knowledge discovery
X
UPG1

                            
2.3 System thinking
X
UPG1

                            
2.4 Attitudes, thought, and learning
X
UPG1

                            
2.5 Ethics, equity, and other responsibilities
X
X
UPG1

                            
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
3.1 Teamwork
X
UPG1

                            
3.2 Communications
X
UPG1

                            
3.3 Communication in foreign languages

                            
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
4.1 External, societal, and environmental context

                            
4.2 Enterprise and business context

                            
4.3 Conceiving, system engineering and management

                            
4.4 Designing
X
UPG1

                            
4.5 Implementing
X
UPG1

                            
4.6 Operating

                            
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

                            
5.2 Economic conditions for knowledge development

                            
5.3 Identification of needs, structuring and planning of research or development projects
X
UPG1

                            
5.4 Execution of research or development projects
X
UPG1

                            
5.5 Presentation and evaluation of research or development projects
X
UPG1

                            

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