Production planning, control and optimisation

The courses introduce the students to the basics in production planning, control and optimisation which are important tools in the development of more material, energy and cost efficient processes.

Optimization (Optimering) introduces students to the basics in optimisation, including the different problem classifications and algorithms to solve the problems. Evolutionary algorithms offers knowledge in optimisation with stochastic methods. Process and production optimization (Process- och produktionsoptimering) provides knowledge on how to solve problems related to the production and cost efficiency and how to distribute tasks optimally. Control of discrete event systems gives basic knowledge in computer aided modeling and control of systems where discrete decisions are made and actions are taken. Neural networks presents an introduction to artificial neural networks and their use in problem solving in engineering.

Courses included in the programme:

= Contact learning
= Online learning
= Blended learning (online & contact learning)
Optimering (424500.0), 5 ECTS. 28.10.–20.12.2019.

Sända ansökan senast 13.10.2019

This course is organised in Swedish!

Studenterna uppnår och visar kunskaper i att självständigt kunna uppställa optimeringsmodeller, välja lämpliga metoder för att lösa dessa, samt även använda mjukvara som implementerar valda algoritmer. En tillräcklig förståelse för de i kursmaterialet givna algoritmerna samt de allmänna optimalitets- villkoren erhålls och påvisas under kursens gång.

Efter fullgjord kurs kan eleven även förklara hur valet av modell och algoritm påverkar möjligheten att uppnå globalt optimala lösningar. Uppnådda färdigheter demonstreras i räkneövningar, en individuell uppgift som eleven själv definierar samt en muntlig tentamen.

Mer information: http://studiehandboken.abo.fi/sv/course/424500.0/1409

Control of discrete event systems (419502.0), 5 ECTS. 28.10.–20.12.2019.

Apply before Oct 13, 2019

The aim of this course is to gain basic knowledge in computer aided modeling and control of discrete event systems.

Themes:

  • automata
  • formal languages
  • blocking
  • controllability
  • observability
  • modularisation
  • algorithms

Upon completion of the course the student knows the modeling of simple discrete events using automata as well as analysis and design of supervisory systems for these.

More information: http://studiehandboken.abo.fi/en/course/419502.0/1377

Process- och produktionsoptimering (411528.0), 5 ECTS. Spring 2020.

This course is organised in Swedish. Course material will be available in English. The exam and assignments can be made in English.

Förhandskrav: Grundkurs i produktionsoptimering eller motsvarande kunskaper.

Kursen behandlar både linjära och icke-linjära optimeringsproblem med diskreta och kontinuerliga variabler. Modelleringsramverken STN och RTN för optimering av batch-baserade produktionsprocesser tas upp och exemplifieras för både linjära och icke-linjära problem. STN och RTN modellerna erbjuder en systematik för att beskriva process- produktionsprocesser och att föra över dem i matematisk form.

Vidare tas ett antal klassiska produktionsoptimeringsexempel upp, t.ex. kvadratiska assigmnetproblem och transportproblem. I kursen behandlas grundprinciperna för några av de vanligaste metoderna för att lösa icke-linjära produktionsoptimeringsproblem. Programvara för att lösa medelstora process- och produktionsoptimeringsproblem används i kursen, både i demonstrationsexempel och i hemarbeten.

Mer information: http://studiehandboken.abo.fi/sv/course/411528.0/2614

Evolutionary algorithms (424511.0), 5 ECTS. Starts in February 2020.

Apply before Jan 15, 2020

Prerequisites: Basic knowledge in any programming language (e.g. Matlab, Pascal, C, Fortran) is required.

In the last 20 years, the growth in interest in stochastic search methods for optimisation has been quite dramatic. Having once been something of a daydream in the field of optimisation, evolutionary algorithms have now attained considerable respect and are extremely popular. They have proven to be good alternatives to the traditional deterministic optimisation methods in many challenging real-life problems. The wide field of different types of applications as well as the relative simplicity of implementation renders them as really attractive choices for optimisation purposes.

The tentative topics to be covered are:

  • Genetic algorithms
  • Differential evolutionary
  • Genetic programming
  • Other evolutionary based search methods
  • Multi-objective optimisation using EAs

More information: http://studiehandboken.abo.fi/en/course/424511.0/1412

Neural networks (424501.0), 5 ECTS. Intensive studies in May 2020.

The course is an introduction to artificial neural networks and their use in problem solving in engineering.

Learning outcomes of the course:

  • To learn the theoretical background of artificial neural networks
  • To understand the theory of neural computation
  • To get acquainted with different neural network architectures and training algorithms
  • To gain partical knowledge on the use of neural networks in problem solving, including the pros and cons of the technique
  • To solve a simple real-world problem with neural networks

More information: http://studiehandboken.abo.fi/en/course/424501.0/2636

Course pages for specific universities:

After the registration you can login to Åbo Akademi’s Moodle.

Professor in charge: Henrik Saxén, Åbo Akademi (henrik.saxen@abo.fi)

Contact person in practical matters: Mikko Helle, Åbo Akademi (mihelle@abo.fi)

Other teachers:

Frank Pettersson, Åbo Akademi

Anders Brink, Åbo Akademi

Hannu Toivonen, Åbo Akademi

Type of study unit

Minor

Credits

5–25 ECTS

Teaching semester

2019–2020

Host university

Åbo Akademi

Open for degree student

Yes

Open for non-student

Yes

Level of studies

Master

Teaching methods

Contact or online learning

Place of contact learning

Turku

Programme suitable for

Courses are suitable for master's level students interested in the topics

Language

English & Swedish

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