Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex

Drake, John H. (2014) Crossover control in selection hyper-heuristics: case studies using MKP and HyFlex. PhD thesis, University of Nottingham.

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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.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Burke, E.K.
Ozcan, E.
Keywords: hyper-heuristics, heuristic programming, knapsack problem, algorithms, search
Subjects: Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
T Technology > T Technology (General)
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 14276
Depositing User: EP, Services
Date Deposited: 18 Nov 2014 10:34
Last Modified: 15 Dec 2017 05:14

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