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Martyn Amos

  1. Parallelization Strategies for Ant Colony Optimisation on GPUs.

    Mon, 01/17/2011 - 16:01 — SomNambul
    Authors: Martyn Amos, Jose M. Cecilia, Jose M. Garcia, Manuel Ujaldon, Andy Nisbet
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    Ant Colony Optimisation (ACO) is an effective population-based meta-heuristic
    for the solution of a wide variety of problems. As a population-based
    algorithm, its computation is intrinsically massively parallel, and it is
    there- fore theoretically well-suited for implementation on Graphics Processing
    Units (GPUs). The ACO algorithm comprises two main stages: Tour construction
    and Pheromone update. The former has been previously implemented on the GPU,
    using a task-based parallelism approach. However, up until now, the latter has
    always been implemented on the CPU.

  2. Genetic algorithms and the art of Zen.

    Wed, 05/26/2010 - 15:01 — SomNambul
    Authors: Martyn Amos, Jack Coldridge
    Subjects: Neural and Evolutionary Computation
    Abstract

    In this paper we present a novel genetic algorithm (GA) solution to a simple
    yet challenging commercial puzzle game known as the Zen Puzzle Garden (ZPG). We
    describe the game in detail, before presenting a suitable encoding scheme and
    fitness function for candidate solutions. We then compare the performance of
    the genetic algorithm with that of the A* algorithm.

  3. Ant Colony Algorithm for the Weighted Item Layout Optimization Problem.

    Tue, 01/26/2010 - 16:01 — SomNambul
    Authors: Yong Liu, Martyn Amos, Yi-Chun Xu, Fang-Min Dong, Ren-Bin Xiao
    Subjects: Neural and Evolutionary Computation
    Abstract

    This paper discusses the problem of placing weighted items in a circular
    container in two-dimensional space. This problem is of great practical
    significance in various mechanical engineering domains, such as the design of
    communication satellites. Two constructive heuristics are proposed, one for
    packing circular items and the other for packing rectangular items. These work
    by first optimizing object placement order, and then optimizing object
    positioning.

  4. Wave propagation in filamental cellular automata.

    Tue, 11/17/2009 - 16:01 — SomNambul
    Authors: Alan Gibbons, Martyn Amos
    Subjects: Formal Languages and Automata Theory
    Abstract

    Motivated by questions in biology and distributed computing, we investigate
    the behaviour of particular cellular automata, modelled as one-dimensional
    arrays of identical finite automata. We investigate what sort of
    self-stabilising cooperative behaviour these can induce in terms of waves of
    cellular state changes along a filament of cells. We discover what the minimum
    requirements are, in terms of numbers of states and the range of communication
    between automata, to observe this for individual filaments.

Math-arch

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