A pyramidal evolutionary algorithm with different inter-agent partnering strategies for scheduling problems

Aickelin, Uwe

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.

Citation

Aickelin, U. (2001). A pyramidal evolutionary algorithm with different inter-agent partnering strategies for scheduling problems

• Conference Name: Genetic and Evolutionary Computation Conference 2001, late-breaking papers volume
• Start Date: Jul 7, 2001
• End Date: Jul 11, 2001
• Publication Date: Jan 1, 2001
• Deposit Date: Oct 2, 2007
• Publicly Available Date: Oct 12, 2007
• Peer Reviewed: Peer Reviewed
• Public URL: http://eprints.nottingham.ac.uk/id/eprint/548
• Copyright Statement: Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf