Supply Chain Optimization, 6 credits

Optimering av försörjningskedjor, 6 hp

TAOP18

Course starting semester

Main field of study

Mathematics Applied Mathematics Industrial Engineering and Management

Course level

Second cycle

Course type

Programme course

Examiner

Nils-Hassan Quttineh

Director of studies or equivalent

Ingegerd Skoglund

Education components

Preliminary scheduled hours: 42 h
Recommended self-study hours: 118 h

Available for exchange students

Yes

Possible deviation from course syllabus/programme syllabus

ECV = Elective / Compulsory / Voluntary

Course offered for		Semester	Period	Timetable module	Language	Campus	ECV
6CDPU	Design and Product Development	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIEI	Industrial Engineering and Management - International, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIEI	Industrial Engineering and Management - International, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIEI	Industrial Engineering and Management - International, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIEI	Industrial Engineering and Management - International, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIEI	Industrial Engineering and Management - International, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CIII	Industrial Engineering and Management, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6KMAT	Mathematics	5 (Autumn 2017)	2	1	English	Linköping, Valla	E
6KMAT	Mathematics (Modelling and Optimization in Economics)	5 (Autumn 2017)	2	1	English	Linköping, Valla	E
6MMAT	Mathematics, Master's programme	3 (Autumn 2017)	2	1	English	Linköping, Valla	E
6MMAT	Mathematics, Master's programme (Modelling and Optimization in Economics)	3 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CMMM	Mechanical Engineering, M Sc in Engineering	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6CMMM	Mechanical Engineering, M Sc in Engineering (Logistics)	9 (Autumn 2017)	2	1	English	Linköping, Valla	E
6MMEC	Mechanical Engineering, Master's programme	3 (Autumn 2017)	2	1	English	Linköping, Valla	E

Main field of study

Mathematics, Applied Mathematics, Industrial Engineering and Management

Course level

Second cycle

Advancement level

A1X

Course offered for

Mathematics
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
Mathematics, Master's programme
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

(valid for students admitted to programmes within which the course is offered)
Basic course in optimization, including network programming. Solid knowledge in computer programming. Recommended prerequisite: Knowledge in optimization modelling language (AMPL or ZIMPL), large scale optimization.

Intended learning outcomes

The course aims to give the students an ability to model optimization problems, and an insight in how mathematical theory can be used to formulate and solve practical problems, with emphasis on applications in supply chain, distribution and transportation planning. The course also aims to give a deeper knowledge about combinatorial optimization, i.e. optimization problems with an underlying graph structure.

Course content

Supply chain optimzation problems, Sequencing and scheduling problems in production planning, Classical machine scheduling problems, Capacitated lot-sizing problem, Transportation and routing problems, Local search/tabu search, Column generation, Ampl-modelling.

Teaching and working methods

The course is built up around a number of cases (practical applications), where the students work with problem analysis, modelling and solving using software as Matlab and Ampl/Cplex. The lectures cover theory and optimization methodology. The cases are discussed and the students present the results of their work. Other practical applications are discussed.

Examination

PRA1

Oral and written presentation of case studies

6 credits

U, 3, 4, 5

Grades

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

Department

Matematiska institutionen

Director of Studies or equivalent

Ingegerd Skoglund

Examiner

Nils-Hassan Quttineh

Course website and other links

http://courses.mai.liu.se/GU/TAOP18

Education components

Preliminary scheduled hours: 42 h
Recommended self-study hours: 118 h

Course literature

Fastställs senare.

Code	Name	Scope	Grading scale
PRA1	Oral and written presentation of case studies	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.

Student rights and obligations (login required)
Linköping University common rules and regulations (in Swedish)

Course literature is preliminary.

Fastställs senare.

Download

Download course literature list as PDF

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize

		I	U	A	Modules
1. DISCIPLINARY KNOWLEDGE AND REASONING
	1.1 Knowledge of underlying mathematics and science (G1X level)		X	X	PRA1
	1.2 Fundamental engineering knowledge (G1X level)			X
	1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
	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	X	X	PRA1
	2.2 Experimentation, investigation, and knowledge discovery
	2.3 System thinking	X			PRA1
	2.4 Attitudes, thought, and learning	X			PRA1
	2.5 Ethics, equity, and other responsibilities
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
	3.1 Teamwork			X	PRA1
	3.2 Communications			X	PRA1
	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		X		PRA1
	4.4 Designing
	4.5 Implementing
	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
	5.4 Execution of research or development projects
	5.5 Presentation and evaluation of research or development projects

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