Type of course

Admission requirements

Bachelor degree in Engineering program in mechanical, electrical power, electronics, mechatronics, material science, industrial engineering, process engineering or other equivalent majors.

In addition, the following requirements must be met:

-minimum 25 credits in mathematics (equivalent to Mathematical Methods 1, 2 og 3), 5 credits in statistics and 7,5 ects i physics on a higher level is required.

Prerequisite(s) Knowledge about linear algebra, classical calculus (maximum/minimum for multi-variable functions) and computer programming at bachelor level.

Application code: 9371

Course content

The course will provide students with knowledge in operations research and decision analysis. The main contents include mathematical optimization and computer-based simulation as well as their applications for solving various real-life industrial problems.

Optimization:

Optimization is prescriptive analytics that concerns the application of mathematical modeling to solve optimization/decision-making problems in the management and operation of complex systems, which may consist of human beings, machines, materials, and capital. The purpose is to help determine the best policy and actions for the allocation of resources. The main techniques are linear programming, integer programming, stochastic programming, non-linear programming, as well as the exact and heuristic methods for solving these mathematical models.

Simulation:

Simulation is descriptive analytics and models real-life systems in a detailed manner, which allows comprehensive scenario analysis, performance measurement, and sometimes, a nice visualization of the system. The purpose is to compare different setups in a more comprehensive and close-to-real-life manner in order to obtain robust decisions and different performance indicators. The main techniques are Monte Carlo simulation, discrete-event simulation, agent-based simulation, and system dynamics.

Applications:

The application areas of optimization and simulation include production planning, product-mix decision-making, facility location, network analysis, project management, routing and scheduling of vehicles and crews, logistics and supply chain management, and blending problems. Furthermore, the historical development, the practical significance, and the limitations of mathematical modeling and simulation are also discussed.

Objectives of the course

Objectives of the course

Knowledge:

The course gives an introduction to operations research and provides the student knowledge of mathematical modeling of complex industrial problems and different basic optimization techniques connected to these models.

Skills:

The candidate will be able to, from a real-life industrial problem or from text-based descriptions, formulate a model to solve the problem and obtain optimal decisions.

The candidate will be able to use different analytical techniques connected to mathematical optimization and simulation.

The candidate will be able to use different software tools to solve optimization problems and perform complex simulations.

General (overall) Qualifications: Based on the given knowledge and skills in mathematical modeling and simulation of complex industrial problems, the candidate shall be able to communicate, solve and improve related issues in future education and working life.

Language of instruction and examination

Teaching methods

Information to incoming exchange students

This course is open for inbound exchange student who meets the admission requirements. Please see the Admission requirements" section".

Master Level

Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412