Malcolm McIlhagga

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This paper describes work on two diierent aspects of the application of genetic algorithms to component design. Namely structural design optimisation and the evolution of free-form 3D shapes. On the rst aspect, a thorough comparison of ten diierent search techniques applied to a wing-box design optimisation problem is described. The techniques used vary(More)
We describe an abstract architecture of adaptive applications, and indicate where we believe crucial design decisions must be made. We illustrate the use of the abstract model in the design of an image proxy, and show where studies are required in determining the appropriate design points. In particular, even though adaptation to resource constraints is(More)
This paper describes a thorough comparison of ten diier-ent search techniques applied to a wing-box design optimisation problem. The techniques used vary from deterministic gradient descent to stochastic Simulated Annealing (SA) and Genetic Algorithms (GAs). The stochastic techniques produced as good solutions as the best found by the deterministic(More)
We describe a comparison between Simulated Annealing (SA), Dispatch Rules (DR), and a Coevolutionary Distributed Genetic Algorithm (DGA) solving a random sample of integrated planning and scheduling (IPS) problems. We found that for a wide range of optimization criteria the DGA consistently outperformed SA and DR. The DGA finds 8-9 unique high quality(More)
This paper describes a Distributed Genetic Algorithm (DGA) which has been used to solve generic scheduling problems. The GA based scheduler allows the user to deene and solve any scheduling problem. It does this using a Scheduling Description Language (SDL). The sort of problem that it might tackle are: job-shop scheduling (JJS), time-tabling, resource(More)
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