- author = "Kevin Sim and Emma Hart and Ben Paechter",
- title = "A Lifelong Learning Hyper-heuristic Method for Bin Packing",
- journal = "Evolutionary Computation",
- year = "2015",
- volume = "23",
- number = "1",
- pages = "37--67",
- month = "Spring",
- keywords = "genetic algorithms, genetic programming, SNGP, AIS, Hyper-heuristics, artificial immune systems, combinatorial optimisation",
- ISSN = "1063-6560",
- broken = "http://www.iidi.napier.ac.uk/binary/dl/file/publicationid/13377145",
-
DOI = "
doi:10.1162/EVCO_a_00121",
- size = "31 pages",
- abstract = "We describe a novel hyper-heuristic system that continuously learns over time to solve a combinatorial optimisation problem. The system continuously generates new heuristics and samples problems from its environment; and representative problems and heuristics are incorporated into a self-sustaining network of interacting entities inspired by methods in artificial immune systems. The network is plastic in both its structure and content, leading to the following properties: it exploits existing knowledge captured in the network to rapidly produce solutions; it can adapt to new problems with widely differing characteristics; and it is capable of generalising over the problem space. The system is tested on a large corpus of 3,968 new instances of 1D bin-packing problems as well as on 1,370 existing problems from the literature; it shows excellent performance in terms of the quality of solutions obtained across the datasets and in adapting to dynamically changing sets of problem instances compared to previous approaches. As the network self-adapts to sustain a minimal repertoire of both problems and heuristics that form a representative map of the problem space, the system is further shown to be computationally efficient and therefore scalable.",
-
notes = "'We have described a continuous learning system
inspired by previous work in the Artificial Immune
System field that is capable of learning to solve a
combinatorial optimisation problem, improves its
performance over time and adapts to changing
environments. The system fuses methods from SNGP
[\cite{jackson:2012:EuroGP} \cite{conf/ppsn/Jackson12}]
which is used to generate novel heuristics with ideas
from immune-network theory...'
PMID: 24512321
Institute for Informatics and Digital Innovation, Edinburgh Napier University, Edinburgh, EH10, UK
Posted Online February 10, 2014.
Presented at GECCO 2014 Hot of the Press Track",
