A Pyramidal Genetic Algorithm for Multiple-Choice Problems

Aickelin, Uwe (2001) A Pyramidal Genetic Algorithm for Multiple-Choice Problems. In: Annual Operational Research Conference 43, Bath.

This is the latest version of this item.

[img] PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB)

Abstract

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Item Type: Conference or Workshop Item (Paper)
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 12 Oct 2007 13:59
Last Modified: 12 Oct 2007 13:59
URI: http://eprints.nottingham.ac.uk/id/eprint/639

Available Versions of this Item

Actions (Archive Staff Only)

Edit View Edit View