Production Planning, Control and Optimization

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

Process optimization introduces students to the basics in optimization, including the different problem classifications and algorithms to solve the problems. Evolutionary algorithms offers knowledge in optimization with stochastic methods. Production optimization and scheduling 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:

Neural Networks (424501.0), 5 ECTS. 1 week Intensive course, preliminary in 05/2019

Apply before Apr 15, 2019

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 info:

Evolutionary Algorithms (424511.0), 5 ECTS. Starts 7.1.2019

Apply before Dec 16, 2018

In the last 20 years, the growth in interest in stochastic search methods for optimization has been quite dramatic. Having once been something of a daydream in the field of optimization, evolutionary algorithms have now attained considerable respect and are extremely popular. They have proven to be good alternatives to the traditional deterministic optimization 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 optimization purposes.

The tentative topics to be covered are indicated below: Genetic Algorithms, Differential Evolutionary, Genetic Programming, Other evolutionary based search methods, Multi-objective optimization using EAs.

Process and Production Optimization (411528.0 Note! The course is lectured in Swedish). Starts 21.1.2019

Apply before Jan 1, 2019

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.

Basics in Production Optimization 411523.0 Note!: Lectured in Swedish. 5 ECTS. Fall 2019.

Målsättningen med kursen är att ge deltagarna verktyg för att lösa linjära produktionsoptimeringsproblem i vilka det ingår både kontinuerliga och diskreta variabler. Kursen fokuserar på problemställningar där kvantitativa metoder har en central roll. I kursen behandlas olika klassiska problem så som produktionsplanering, lager-, transport-, distribution- och schemaläggningsproblem. För att lösa problemen används såväl allmänt tillgänglig programvara som specialprogramvara för optimering.


More info:

Control of discrete event systems (419502.0), 5 ECTS. Fall 2019.

To gain basic knowledge in computer aided modeling and control of discrete event systems. Automata, formal languages, blocking, controllability, observability, modularisation and algorithms.

More info:

Course pages for specific universities:

After the registration:

Professor in charge: Henrik Saxén, Åbo Akademi (

Contact person in practical matters: Mikko Helle, Åbo Akademi (

Other teachers:

Frank Pettersson, Åbo Akademi

Anders Brink, Åbo Akademi and

Hannu Toivonen, Åbo Akademi

Type of study unit:



5-20 ECTS

Teaching semester


Host university

Åbo Akademi

Open for non student


Level of studies



Contact learning or online



Programme suitable for

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


English and Swedish

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