T1: Tutorial on Heuristic Optimization
Partners involved:
Univ. de Genève (Local Organizer), Univ. of Giessen, Univ. of Essex.
Date and location:
24/09/2007 - 29/09/2007 in Sils Maria, Switzerland.
Motivation and objectives:
The tutorial provides a structured overview of optimization problems and solution techniques. The standard techniques for optimization of differentiable functions together with practical issues will be recalled. The presentation of some relevant optimization problems where classical methods fail to work will motivate the introduction of the heuristic optimization paradigm with a general overview and a classification for hybrid methods. The remaining lectures introduce to heuristic optimization methods and emphasize practical and implementation related aspects.
Organization
Two days with six lectures of 90 minutes and one afternoon “hands on” session.
- Overview of optimization problems and standard solution methods.
- The heuristic optimization paradigm: Overview and classification of heuristics.
- Local search methods: Simulated annealing, threshold accepting, tabu search.
- Population based methods: Evolution based and genetic algorithms; ant systems and ant colony optimization; memetic algorithms.
- Monte Carlo methods: Random variable generation; quasi-Monte Carlo methods.
- Examples of implementations.
- “Hands on” session in the computer laboratory.