Malcolm McIlhagga

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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)
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 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)
This paper outlines a coevolutionary distributed genetic algorithm for tackling an integrated manufacturing planning and scheduling problem. In this multispecies ecosystems model, the genotype of each species represents a feasible manufacturing (process) plan for a particular component to be manufactured in the machine shop. Separate populations evolve(More)
In the Lowband project at the University of Sussex, we are building an architecture in which multimedia data is turned into intelligent active objects which can control their own disposition and adapt to transmit and display themselves in an appropriate manner, according to the constraints of network bandwidth and display capabilities. The system is being(More)
This CSRP describes a Distributed Genetic Algorithm (DGA) which has been used to solve generic scheduling problems. The system is capable of allowing its user to deene and solve any scheduling problem using a Scheduling Description Language (SDL), e.g. job-shop scheduling, time-tabling, resource sequencing etc. We will describe a unique encoding/decoding(More)
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