Steven David Prestwich

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The IMPASSE class of local search algorithms have given good results on many vertex colouring benchmarks. Previous work enhanced IMPASSE by adding the constraint programming technique of forward checking, in order to prune colouration neighbourhoods during search. On several large graphs the algorithm found the best known colourings. This paper extends the(More)
Two contrasting search paradigms for solving combinatorial problems are systematic backtracking and local search. The former is often effective on highly structured problems because of its ability to exploit consistency techniques, while the latter tends to scale better on very large problems. Neither approach is ideal for all problems, and a current trend(More)
Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework for combined reasoning about these three kinds of information. In this paper we study how to exploit classical and soft constraint solvers for handling qualitative preference(More)
Covering arrays can be applied to the testing of software, hardware and advanced materials, and to the effects of hormone interaction on gene expression. In this paper we develop constraint programming models of the problem of finding an optimal covering array. Our models exploit global constraints, multiple viewpoints and symmetry-breaking constraints. We(More)
Partial deduction systems must be guided by an unfolding strategy, telling them which atoms to unfold and when to stop unfolding. Online strategies exploit knowledge accumulated during the unfolding itself, for example in a goal stack, while offline strategies are fixed before unfolding begins. Online strategies are more powerful, but a major overhead for(More)