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Høst 2021

INE-3800 Operations Research 1 - 5 stp


The course is administrated by

Institutt for industriell teknologi

Type of course

The course can be taken as a single course.

Course overlap

SMN6196 Operations Research 1 5 stp

Course contents

Linear optimisation:

Linear optimization concerns the application of mathematical modelling of complex linear problems arising in management and operation of complex systems, consisting of human beings, machines, materials and capital. The purpose is to help management people and problem solvers to determine its policy and actions by allocation of resources. Considered techniques are: Linear programming, integer programming, network analysis, and transportation problems. Applications: Production planning, product-mix decision making, routing and scheduling of vehicles and crews, blending problems. Furthermore, the historical development, the practical significance and the limitations of the linear mathematical modelling are being discussed.

Industrial Technology Nonlinear Optimisation:

Nonlinear optimisation considers problems to find best (in a well-defined sense) solutions with in general nonlinear problems. Selected topics are the application of nonlinear optimisation in Industrial Technology, solution of nonlinear optimisation problems with both discrete and continuous variables, special optimisation problems, graphical optimisation, software tools for nonlinear optimisation, use of experience-based systems, systems analysis via nonlinear optimisation, optimization algorithms and heuristics methods.


Application deadline

Applicants from countries within EU/EEA: June 1st for the autumn semester and December 1st for the spring semester.

Exchange students and Fulbright students: 1 October for the spring semester and 15 April for the autumn semeste


Admission requirements

A relevant undergraduate Bachelor Engineering program in mechanical, electrical power, electronics, mechatronics, material science, industrial engineering, process engineering or other equivalent majors with minimum 25 credits mathematics, 5 credits statistics, 7,5 credits physics

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

Application code: 9371


Objective of the course

Objectives of the course

Knowledge:

The course give and introduction to operations research and provides the student knowledge of mathematical modelling of complex linear and nonlinear industrial problems and different basic optimization techniques connected to these models.

Skills:

The candidate will be able to, from a text based description, set up linear and nonlinear

models to optimize industrial problems.

The candidate will have the ability to use different basic optimisation techniques connected to linear and nonlinear models.

The candidate will have the ability to use different software as tools for optimisation of linear and nonlinear models.

General (overall) Qualifications: Based on the given knowledge and skills in mathematical modelling of linear and nonlinear problems the candidate shall be able to communicate, solve and improve related problems in future education and working life


Language of instruction

English

Teaching methods

The lectures for the course are divided on two weeks in the autumn. It is not possible to take the exam in the spring.

Assessment

Mandatory tasks:

Linear optimisation:

Five compulsory exercises. Each delivered as PechaKucha 20x20.

Industrial Technology Nonlinear Optimisation:

Four compulsory exercises. Each delivered as PechaKucha 20x20.

Examination and assessment

Three days individual home exam.

The task will be handed out through Wiseflow at       09:00, xx.xx.xxxx

The delivery will be a PechaKucha 20x20 at              16:00, xx.xx.xxxx

Grading will be done by using A-F grading scale, where F is a fail.

The grade will be based solely on the result of the examination.

A re-sit exam will be arranged for this course.