Sequence Analysis-based Hyper-heuristics for Water Distribution Network Optimisation. (2015)

• Record Type: Journal Article
• Authors: Kheiri, Ahmed; Keedwell, Edward; Gibson, Michael J.; Savic, Dragan
• Is Part Of: Procedia engineering. Volume 119(2015)
• Page Start: 1269
• Page End: 1277
• Publication Date: 2015
• Subjects: Hyper-heuristic -- Water Distribution Network -- Hidden Markov Model; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Conference proceedings; Periodicals; 620.005
• DOI: 10.1016/j.proeng.2015.08.993
• Languages: English
• ISSNs: 1877-7058

Abstract

Abstract: Hyper-heuristics operate at the level above traditional (meta-)heuristics that 'optimise the optimiser'. These algorithms can combine low level heuristics to create bespoke algorithms for particular classes of problems. The lowlevel heuristics can be mutation operators or hill climbing algorithms and can include industry expertise. This paper investigates the use of a new hyper-heuristic basedon sequence analysis in the biosciences, to develop new optimisers that can outperform conventional evolutionary approaches. It demonstrates that the new algorithms develop high quality solutions on benchmark water distribution network optimisation problems efficiently, and can yield important information about the problem search space.