Andrew Tuson

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In the majority of genetic algorithm implementations, the operator settings are fixed throughout a given run. However, it has been argued that these settings should vary over the course of a genetic algorithm run--so as to account for changes in the ability of the operators to produce children of increased fitness. This paper describes an investigation into(More)
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— This paper describes a novel, principled approach to real-valued dataset reduction based on fuzzy and rough set theory. The approach is based on the formulation of fuzzy-rough discernibility matrices, that can be transformed into a satisfiability problem; an extension of rough set approaches that only apply to discrete datasets. The fuzzy-rough hybrid(More)
Scheduling in chemical flowshops is one of a number of important industrial problems which are potentially amenable to solution using the genetic algorithm. However the problem is not trivial: flowshops run continuously, and for efficient operation those controlling them must be able to adjust the order in which products are made as new requests are(More)
Shape optimisation is a hard problem from the eld of Mechanical Engineering with the potential for signiicant cost savings if successfully performed. In the past, evolutionary optimisation approaches have proved successful. In those studies, a form of the shape was assumed, and its parameters optimised. An alternative is a voxel (N-dimensional pixel) based(More)