Call number: LD2668 .T4 1933 B81

Call number: LD2668 .T4 1937 G71

Evolutionary search algorithms (ESAs from now on) are iterative problem solvers developed with inspiration from neo-Darwinian survival of the fittest genes. This thesis looks at the core issues surrounding ESAs and is a step towards building a rational methodology for their effective use. Currently there is no such method of best practice rather the whole process of designing and using ESAs is seen as more of a black art than a tried and tested engineering tool. Consequently, many non-practitioners are sceptical of the worth of ESAs as a useful tool at all. Therefore the first task of the thesis is to layout the reasons, from computational theory, why ESAs can be a potentially powerful tool. In this context the theory of NP-completeness is introduced to ground the discussions throughout the thesis. Then a simple framework for describing ESAs is developed to form another cornerstone of these later discussions. From here there are two main themes of the thesis. The first theme is that the No Free Lunch result requires us to take a problem centric, as opposed to algorithm centric, perspective on ESA research. The second major theme is the argument that whole algorithms and traditional computer science problem classes are the wrong level of granularity for the focus of our research. Instead we should be researching empirical questions of search bias at the granularity of the components of search algorithms. Furthermore, we should be finding empirical evidence to demonstrate that our granularity of analytic class is such that one analytic class maps onto one search bias class. We will see that this can mean that we have to sub-divide our classic computer science problems classes into smaller sub-classes. The hope is that we can find analytic distinctions that will sub-divide the instances along lines that match the divisions between the various empirically discoverable search bias classes. The intention is to develop our knowledge until we get one analytic class to map into one empirical class. If we have strong empirical evidence to suggest that this has been achieved then we have good grounds on which to confidently use this knowledge to predict the effective search biases required for new problem instances. In the last two chapters of the thesis we demonstrated these ideas on various instances of the euclidean TSP problem class

As a high quality green belt in the city, a city's waterfront landscape is can be a liveable and comfortable place. For citizens, it is also an attractive place to live in. A good city waterfront landscape can be updated and maintained by itself. Therefore, we can not treat the urban waterfront area as just a beautiful landscape in aesthetic terms, but we should also understand it in deeper and broader dimensions. The urban waterfront landscape directly affects the urban structure, the urban ecological environment and the life quality of the urban residents. By analysizing the two cases, Western Harbor in Malmö and Jinji Lake in Suzhou China, we can draw some interesting conclusions about waterfront landscape. Through the discussion of this subject, I aim for an understanding of the urban waterfront landscape as a harmonious system with the artificial and natural landscapes working together, based on scientific and artistic aspects.

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This work develops a conceptual framework for modeling and simulating spatial dynamics. The framework links modeling of time variability with spatial variability. With current modeling in environmental analysis taking place at the discrete level (modeling fire, hiker behavior, or watershed run-off), it is the task of this thesis to provide a conceptual framework for integration of these discrete components in a systems like simulation environment for modeling their interactions through time. It explores the utility of the discrete event simulation framework developed by Zeigler (1976, 1984) for linking different environmental models in an interactive environment. It expands Zeigler's framework by linking cellular automata methodology to the discrete event methodology. Finally, this thesis demonstrates event modeling and simulation concepts used in the framework.

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