At a Glance

This training provides the necessary fundamentals of mathematical programming and useful tips for good modelling practice in order to construct simple optimization models.

SYLLABUS

Module 1 - The Big Picture

• • • What is Operations Research?
    • What is Optimization?
    • Optimization models

Module 2 - Linear Programming

• • • Introduction to Linear programming
    • A production problem : Part 1 - Writing the model
    • A production problem : Part 2 - Finding a solution
    • A production problem : Part 3 - From feasibility to unboundedness
    • Algorithms for solving linear programs : Part 1 - The Simplex and Dual Simplex Algorithm
    • Algorithms for solving linear programs : Part 2 - The Simplex and Barrier methods

Module 3 - Network Models

• • • Introduction to Network Models
    • The Transportation problem
    • The Transshipment problem
    • The Assignment problem
    • The shortest path problem
    • Critical path analysis

Module 4 - Beyond simple LP

• • • Nonlinearity and Convexity
    • Piecewise linear programming
    • Integer programming
    • The branch and bound method
    • Quadratic Programming

Module 5 - Modelling Practice

• • • Modelling the real world
    • The importance of Sparsity
    • Tips for better models

GENERAL INFORMATION

• • • This course is free.
    • It is self-paced.
    • It can be taken at any time.
    • It can be audited as many times as you wish.

RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE

• • • None

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Course Staff

 

Shirley de Jonk

Shirley de Jonk, PhD is a former UK university lecturer in Information Systems and researcher in Mathematical Programming. Today she is an Information Developer at IBM France working on IBM Decision Optimization products.