Supply Chain Optimization, 6 credits

Optimering av försörjningskedjor, 6 hp

TAOP18

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

Nils-Hassan Quttineh

Education components

Preliminary scheduled hours: 44 h
Recommended self-study hours: 116 h

Available for exchange students

Yes
Course offered for Semester Period Timetable module Language Campus ECV
6CDPU Design and Product Development 9 (Autumn 2018) 2 1 English Linköping E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Chinese 9 (Autumn 2018) 2 1 English Linköping E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - French 9 (Autumn 2018) 2 1 English Linköping E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - German 9 (Autumn 2018) 2 1 English Linköping E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Japanese 9 (Autumn 2018) 2 1 English Linköping E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering - Spanish 9 (Autumn 2018) 2 1 English Linköping E
6CIII Industrial Engineering and Management, M Sc in Engineering 9 (Autumn 2018) 2 1 English Linköping E
6KMAT Mathematics, Bachelor´s Programme 5 (Autumn 2018) 2 1 English Linköping E
6KMAT Mathematics, Bachelor´s Programme (Modelling and Optimization in Economics) 5 (Autumn 2018) 2 1 English Linköping E
6MMAT Mathematics, Master's Programme 3 (Autumn 2018) 2 1 English Linköping E
6MMAT Mathematics, Master's Programme (Modelling and Optimization in Economics) 3 (Autumn 2018) 2 1 English Linköping E
6CMMM Mechanical Engineering, M Sc in Engineering 9 (Autumn 2018) 2 1 English Linköping E
6CMMM Mechanical Engineering, M Sc in Engineering (Logistics) 9 (Autumn 2018) 2 1 English Linköping E
6MMEC Mechanical Engineering, Master's Programme 3 (Autumn 2018) 2 1 English Linköping E
6MMEC Mechanical Engineering, Master's Programme (Manufacturing Engineering) 3 (Autumn 2018) 2 1 English Linköping E
ECV = Elective / Compulsory / Voluntary

Main field of study

Mathematics, Applied Mathematics, Industrial Engineering and Management

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Mathematics, Master's Programme
  • Mathematics, Bachelor´s Programme
  • 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

(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

PRA1Oral and written presentation of case studies6 creditsU, 3, 4, 5

Grades

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

Other information

Supplementary courses: Mathematical Optimization

Department

Matematiska institutionen

Director of Studies or equivalent

Nils-Hassan Quttineh

Examiner

Nils-Hassan Quttineh

Course website and other links

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

Education components

Preliminary scheduled hours: 44 h
Recommended self-study hours: 116 h

Course literature

Other

  • Kursmaterial från institutionen
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. 

Other

Kursmaterial från institutionen

Note: The course matrix is not fully translated to English.

I U A Modules Comment
1. ÄMNESKUNSKAPER
1.1 Kunskaper i grundläggande matematiska och naturvetenskapliga ämnen
X
X
PRA1
Använder algebra- och analyskunskaper
1.2 Kunskaper i grundläggande (motsvarande G1X) teknikvetenskapliga ämnen
X
Vid utveckling av optimeringsmodeller
1.3 Fördjupade kunskaper (motsvarande G2X), metoder och verktyg inom något/några teknik- och naturvetenskapliga ämnen
1.4 Väsentligt fördjupade kunskaper (motsvarande A1X), metoder och verktyg inom något/några teknik- och naturvetenskapliga ämnen
1.5 Insikt i aktuellt forsknings- och utvecklingsarbete
2. INDIVIDUELLA OCH YRKESMÄSSIGA FÄRDIGHETER OCH FÖRHÅLLNINGSSÄTT
2.1 Analytiskt tänkande och problemlösning
X
X
X
PRA1
Centralt för opt, kännetecknar anv. av opt.
2.2 Experimenterande och undersökande arbetssätt samt kunskapsbildning
2.3 Systemtänkande
X
PRA1
Centralt för opt, kännetecknar anv. av opt.
2.4 Förhållningssätt, tänkande och lärande
X
PRA1
Kritiskt tänkande
2.5 Etik, likabehandling och ansvarstagande
3. FÖRMÅGA ATT ARBETA I GRUPP OCH ATT KOMMUNICERA
3.1 Arbete i grupp
X
PRA1
Projektarbete i grupper om 2 studenter
3.2 Kommunikation
X
PRA1
Muntl. samt skriftliga rapport. av projektarb.
3.3 Kommunikation på främmande språk
4. PLANERING, UTVECKLING, REALISERING OCH DRIFT AV TEKNISKA PRODUKTER OCH SYSTEM MED HÄNSYN TILL AFFÄRSMÄSSIGA OCH SAMHÄLLELIGA BEHOV OCH KRAV
4.1 Samhälleliga villkor, inklusive ekonomiskt, socialt och ekologiskt hållbar utveckling för kunskapsutveckling
4.2 Företags- och affärsmässiga villkor
4.3 Att identifiera behov samt strukturera och planera utveckling av produkter och system
X
PRA1
Tränar matematisk modellering
4.4 Att konstruera produkter och system
4.5 Att realisera produkter och system
4.6 Att ta i drift och använda produkter och system
5. PLANERING, GENOMFÖRANDE OCH PRESENTATION AV FORSKNINGS- ELLER UTVECKLINGSPROJEKT MED HÄNSYN TILL VETENSKAPLIGA OCH SAMHÄLLELIGA BEHOV OCH KRAV
5.1 Samhälleliga villkor, inklusive ekonomiskt, socialt och ekologiskt hållbar utveckling
5.2 Ekonomiska villkor för kunskapsutveckling
5.3 Att identifiera behov samt strukturera och planera forsknings- eller utvecklingsprojekt
5.4 Att genomföra forsknings- eller utvecklingsprojekt
5.5 Att redovisa och utvärdera forsknings- eller utvecklingsprojekt

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