Nicholas J. Radcliffe

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A rigorous formulation of the generalisation of schema analysis known as forma analysis is presented. This is shown to provide a direct mechanism for harnessing knowledge about a search space, codified through the imposition of equivalence relations over that space, to generate a genetic representation and operators. It is shown that a single(More)
This paper seeks to document the current state of the art in ‘uplift modelling’—the practice of modelling the change in behaviour that results directly from a specified treatment such as a marketing intervention. We include details of the SignificanceBased Uplift Trees that have formed the core of the only packaged uplift modelling software currently(More)
Intrinsic parallelism is shown to have application beyond schemata and o-schemata. More general objects called formae are introduced and general operators which manipulate these are introduced and discussed. These include random, respectful recombination. The extended formalism is applied to various common representations and standard operators are analysed(More)
The conventional understanding of genetic algorithms depends upon analysis by schemata and the notion of intrinsic parallelism. For this reason, only k-ary string representations have had any formal basis and non-standard representations and operators have been regarded largely as heuristics, rather than principled algorithms. This paper extends the(More)
This paper describes a novel method for attacking constrained optimisation problems with evolutionary algorithms, and demonstrates its effectiveness over a range of problems. COMOGA (Constrained Optimisation by MultiObjective Genetic Algorithms) combines two evolutionary techniques for multiobjective optimisation with a simple regulatory mechanism to(More)
A formal, representation-independent form of a memetic algorithm— a genetic algorithm incorporating local search—is introduced. A generalised form ofN -point crossover is defined together with representation-independent patching and hill-climbing operators. The resulting formal algorithm is then constructed and tested empirically on the travelling sales-rep(More)
Forma analysis is applied to the task of optimising the connectivity of a feed- forward neural network with a single layer of hidden units. This problem is reformulated as a multiset optimisation problem, and techniques are developed to allow principled genetic search over fixed- and variable-size sets and multisets. These techniques require a further(More)
The past twenty years has seen a rapid growth of interest in stochastic search algorithms, particularly those inspired by natural processes in physics and biology. Impressive results have been demonstrated on complex practical optimisation problems and related search applications taken from a variety of fields, but the theoretical understanding of these(More)
This paper presents a new technique for handling constraints within evolutionary algorithms, and demonstrates its effectiveness on a real-world, constrained optimisation problem that arises in the design of gas-supply networks. The technique, which we call the COMOGA method (Constrained Optimisation by Multi-Objective Genetic Algorithms), borrows two(More)