Course description
The main goal of the course is to expose the students to these advanced methods and their uses, and show how tackling a complex engineering problem requires integrating advanced tools from many fields.

The majority of the course will be devoted to one grand example. This example takes a main question of finding an optimal maintenance policy of a manufacturing system and breaks it into pieces. The solution of the problem brings tool from:
• Modeling – to quantify the times and features as variables.
• Stochastic processes – to model the general system, approximate it by a `simple’ system, and analyze it
• Simulation – to estimate the goodness of the approximation
• Optimization – to find the optimal resource allocation via a proper optimization algorithm
• Statistical modeling and inference – to validate the effectiveness of the algorithm

Methodology
During the course we will rehearse briefly the basic concepts of random variables, Markov chain, optimization and statistical tests. We will then study advanced tools that rely on these concepts and extend them.

Prerequisite
Introductory courses in statistical inference, probability and OR.

More detailed information on the course: GP-OML-Modeling, queueing analysis, simulation and optimization of manufacturing systems I

Lecturer: Dr. Yoav Kerner

Course dates: 28 November & 5 December 2018

Time: 10.00 -16.00 h.

Location:  Utrecht, Boswell-Beta, Laan van Puntenburg 2A

ECTS: 0.5 (attendance) – 2 (attendance + assignment)

Participation: free for TRAIL/Beta/OML members and PhD students of participating faculties

Registration: CLICK HERE

This course is part of the GP-OML program (www.GP-OML.nl)