Crossover Control in Selection Hyper-heuristics: Case Studies using MKP and HyFlex

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@PhdThesis{Drake:thesis,
  author =       "John H. Drake",
  title =        "Crossover Control in Selection Hyper-heuristics: Case
                 Studies using {MKP} and {HyFlex}",
  school =       "School of Computer Science, The University of
                 Nottingham",
  year =         "2014",
  address =      "UK",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming,
                 hyper-heuristics, heuristic programming, knapsack
                 problem, algorithms, search",
  URL =          "http://eprints.nottingham.ac.uk/id/eprint/14276",
  URL =          "http://eprints.nottingham.ac.uk/14276/1/thesis.pdf",
  size =         "199 pages",
  abstract =     "Hyper-heuristics are a class of high-level search
                 methodologies which operate over a search space of
                 heuristics rather than a search space of solutions.
                 Hyper-heuristic research has set out to develop methods
                 which are more general than traditional search and
                 optimisation techniques. In recent years, focus has
                 shifted considerably towards cross-domain heuristic
                 search. The intention is to develop methods which are
                 able to deliver an acceptable level of performance over
                 a variety of different problem domains, given a set of
                 low-level heuristics to work with.

                 This thesis presents a body of work investigating the
                 use of selection hyper-heuristics in a number of
                 different problem domains. Specifically the use of
                 crossover operators, prevalent in many evolutionary
                 algorithms, is explored within the context of
                 single-point search hyper-heuristics. A number of
                 traditional selection hyper-heuristics are applied to
                 instances of a well-known NP-hard combinatorial
                 optimisation problem, the multidimensional knapsack
                 problem. This domain is chosen as a benchmark for the
                 variety of existing problem instances and solution
                 methods available. The results suggest that selection
                 hyper-heuristics are a viable method to solve some
                 instances of this problem domain. Following this, a
                 framework is defined to describe the conceptual level
                 at which crossover low-level heuristics are managed in
                 single-point selection hyper-heuristics. HyFlex is an
                 existing software framework which supports the design
                 of heuristic search methods over multiple problem
                 domains, i.e. cross-domain optimisation. A traditional
                 heuristic selection mechanism is modified in order to
                 improve results in the context of cross-domain
                 optimisation. Finally the effect of crossover use in
                 cross-domain optimisation is explored.",
  notes =        "Supervisors: Ender Ozcan",
}

Genetic Programming entries for John H Drake

Citations