• Optimization (TZLM5300-3001),
         24.10.2022 – 09.12.2022,  3 cr  (TLS20S1) — Face-to-face +-
    Learning outcomes of the course
    Purpose of the course
    After the course you will understand how engineers use mathematical models and tools to find the best, fastest or most economical way to achieve the desired operative goals.

    Learning objectives
    You know basic principles and methods of optimization and networks. You can construct an optimization or network model of a work-related problem and solve it by using a computer.
    Prerequisites and co-requisites
    You can find the extreme values of a function by differentiation. You know the normal distribution.
    Course contents
    Principles and methods of linear and nonlinear optimization
    Fundamental graph theory and network optimization algorithms
    Applications in operative decision making
    Using Excel
    Assessment criteria
    Assessment criteria - grade 1 and 2
    Sufficient 1
    You have achieved the desired goals. You know a few of the concepts and methods and how to apply them in familiar situations but your reasoning is often deficient and you make mistakes in calculations.

    Satisfactory 2
    You have achieved the desired goals. You know many of the concepts and methods and how to apply them in familiar situations but your reasoning is sometimes deficient or you make mistakes in calculations.
    Assessment criteria - grade 3 and 4
    Good 3
    You have achieved the desired goals. You know most of the concepts and methods and how to apply them in familiar situations showing often the ability to reason completely and calculate flawlessly

    Very good 4
    You have achieved the desired goals. You know most of the concepts and methods and how to apply them in new situations showing in most cases the ability to reason completely and calculate flawlessly.
    Assessment criteria - grade 5
    Excellent 5
    You have achieved the desired goals. You know all the concepts and methods and how to apply them in new situations showing always the ability to combine things, reason completely and calculate flawlessly.
    Language of instruction

    Finnish

    Planned learning activities, teaching methods and guidance

    The contact lessons are in a computer class and involve use of computers. The theory should be independently acquired before class exercises. The learning is accomplished by assignments where theory is put into practice.

    Lecturer(s)

    Pasi Lehtola

    Learning materials and recommended literature

    Taylor, B. W. (2018) Introduction to Management Science. Pearson
    Other material accessible in Moodle

    Lecturer(s)

    Pasi Lehtola

    Campus

    Main Campus

    Exam dates and re-exam possibilities

    The date and execution of the exam will be announced in the beginning of the course.

    Timing

    24.10.2022 - 09.12.2022

    Learning assignments and student workload

    Contact lessons about 20 hours
    Independent study about 20 hours
    Learning tasks about 20 hours

    Enrollment

    01.08.2022 - 25.08.2022

    Groups
    • TLS20S1
    Alternative learning methods

    The admission procedures are described in the degree rule and the study guide.

    Small groups
    • TLS20SA (: 30. : 0.)
    • TLS20SB (: 30. : 0.)
    Seats

    0 - 50

    Assessment methods

    The assessment is based on learning tasks and exams.

    An equivalent course in English TZLM5300-3002 Optimization.

    Open AMK: at most 5 students if there are seats in the classroom.

    Degree Programme

    Bachelor's Degree Programme in Logistics

    Mode of delivery

    Face-to-face

    Credits
    • 3 cr
    Unit

    School of Technology