Stochastic optimization using algebraic modelling languages

BAN437 Stochastic optimization using algebraic modelling languages

Spring 2024

  • Topics

    The seminar will introduce uncertainty, in the form of random variables, into optimization models. The focus will be on why we need this, and what can go wrong with deterministic modeling. We shall use professional software - AMPL - to formulate and solve simple numerical models, so as to see how solutions change to adjust to the uncertain future. In other words, see how tactical and strategic decisions change to facilitate operational handling of uncertainty. The technical level of the course is limited, we focus on concepts and simple examples. 

  • Learning outcome

    By the end of this seminar the students

    Knowledge

    • are able to explain and discuss key concepts in decision making under uncertainty, and understand why deterministic modeling does not deliver what it promises
    • are able to verbally formulate relevant research questions where uncertainty in optimization is involved

    Skills

    • are able to algebraically formulate simple optimization models involving uncertainty
    • are able to solve simple problems using high-level optimization software, like GAMS or AMPL

    General competence

    • are able to use computational tools for implementing and solving simple decision models involving uncertainty 

  • Teaching

    One week with a mix of teaching and work on the implementation of some simple models using AMPL.

  • Required prerequisites

    Students need to have taken a basic course in optimization, operations research, management science, industrial engineering or something similar so as to be able to read and write simple optimization models, including the use of high-level software at a basic level (like AMPL or GAMS - not just Excel). For NHH students, BAN402 is a perfect background.

  • Credit reduction due to overlap

    None.

  • Compulsory Activity

    Mandatory attendance.

  • Assessment

    A group presentation (2-5 students in a group) on a given topic.

    Due to the change in assessment spring 2024, previously acquired course approval in BAN437 is no longer valid.

  • Grading Scale

    Pass-Fail.

  • Computer tools

    Standard laptop, AMPL modelling language with solvers CPLEX, Gurobi and MINOS (licenses will be provided during the course).

  • Literature

    To be given in Canvas

Overview

ECTS Credits
2.5
Teaching language
English
Semester

Spring. Will be offered Spring 2024 (first week of the semester).

Course responsible

Professor Stein W. Wallace, Department of Business and Management Science