An improved immune inspired hyper-heuristic for combinatorial optimisation problems.

Sim, Kevin; Hart, Emma

Abstract

The meta-dynamics of an immune-inspired optimisation sys- tem NELLI are considered. NELLI has previously shown to exhibit good performance when applied to a large set of optimisation problems by sustaining a network of novel heuristics. We address the mechanisms by which new heuristics are defined and subsequently generated. A new representation is defined, and a mutation-based operator inspired by clonal- selection introduced to control the balance between explo- ration and exploitation in the generation of new network elements. Experiments show significantly improved perfor- mance over the existing system in the bin-packing domain. New experiments in the job-scheduling domain further show the generality of the approach.

Citation

Sim, K., & Hart, E. (2014). An improved immune inspired hyper-heuristic for combinatorial optimisation problems. In C. Igel (Ed.), Proceedings of GECCO 2014 (Genetic and Evolutionary Computation Conference) (121-128). https://doi.org/10.1145/2576768.2598241

• Start Date: Jul 12, 2014
• End Date: Jul 16, 2014
• Publication Date: Jul 12, 2014
• Deposit Date: Jul 1, 2014
• Publicly Available Date: May 15, 2017
• Publisher: Association for Computing Machinery (ACM)
• Peer Reviewed: Peer Reviewed
• Pages: 121-128
• Book Title: Proceedings of GECCO 2014 (Genetic and Evolutionary Computation Conference)
• ISBN: 978-1-4503-2662-9
• DOI: https://doi.org/10.1145/2576768.2598241
• Keywords: Immune-inspired optimisation system; NELLI; novel heuristics
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/6899
• Publisher URL: http://dx.doi.org/10.1145/2576768.2598241