During the early stages of engineering system design the engineer is generally faced with multiple discrete choices relating to the major elements which define the overall structure of the system. However, in many cases the system cannot be adequately described in terms of discrete decisions alone. Continuous variables that to some extent describe the characteristics of each discrete design configuration need to be included to achieve a meaningful definition. This creates a search/optimisation problem of considerable complexity as each set of continuous variables will be dependent upon the particular configuration that they describe and the constituent variables of these sets may differ from one configuration to another as illustrated in the simple hierarchy of Figure 7.1. The result is a set of differing, dependent, continuous design spaces each of which describes a particular discrete design option/configuration. In this high-level whole-system design (WSD) situation an efficient search strategy is required to provides a multi-level search capability that can negotiate the discrete hierarchy, efficiently sampling the different continuous design spaces in order to identify those configurations that offer best potential. If such a strategy can be developed it would be possible to explore a far greater number of whole-system design solutions than would be possible from a more traditional heuristic approach. The result would be a high-level, decision support tool that may reduce lead times during conceptual/preliminary stages of design whilst allowing a more extensive search of the available design alternatives within budget and time constraints. This will result in the identification of competitive system configurations that may have been overlooked during the problem decomposition processes of heuristic design. The developed strategies would enable the engineer to rapidly survey the potential of diverse regions of the hierarchy within time constraints thereby avoiding a compromise of search space potential by rapidly returning to known regions and prematurely concentrating search effort in a small subset of the complex solution space.


Tunnel Length Hydropower System Discrete Path Adaptive Computing Continuous Design Variable 
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Copyright information

© Springer-Verlag London 2001

Authors and Affiliations

  • Ian C. Parmee
    • 1
  1. 1.Advanced Computational TechnologiesExeterUK

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