Heuristic Optimization
CPSC 599, Summer 2007
What this course is about ...
Parameter optimization is an important component of various disciplines (i.e., mathematics, life sciences, kinesiology, economics, engineering, etc.), that form an important part of our day-to-day life. As a result, a wide range of both traditional and non-traditional algorithmic approaches have been introduced to solve various optimization problems.
Evolutionary algorithms (including genetic algorithms, evolution strategies, genetic programming, and evolutionary programming) represent a category of newer (so called non-traditional) heuristic search methods that offer tremendous promise. These population-based algorithms have drawn inspirations from nature, and utilize principles of evolution. Swarm-based optimization techniques represent another set of non-traditional algorithmic approaches inspired by
social behaviours of organisms such as birds (i.e., particle swarm optimization) and ants (i.e., ant colony optimization). These non-traditional swarm approaches are also now entering a stage of optimization, and do remarkably well solving real-world optimization problems. Each of these different methods has its own strengths and weaknesses.
In this year's Heuristic Optimization course we will explore the following topics :
• Traditional Methods,
• Swarm Optimization Algorithms, and
• Evolutionary Algorithms
Instructors
ICT 716, ICT Building
Department of Computer Science
University of Calgary
Email: {khemka, jacob}[at]cpsc[dot]ucalgary[dot]ca
Phone: 220-8410
You can talk to us during our office hours (4pm - 5pm on Tuesday and Thursday).
You are also welcome at any other time to drop by our office. However, we recommend that you make an appointment with us beforehand, to make sure that we have enough time for you.
