MIXED CONTINUOUS VARIABLE AND CATALOG SEARCH USING GENETIC ALGORITHMS

In this paper a general design and catalog representation is proposed and implemented. The representation is applied to mixed continuous variable and catalog search using genetic algorithms. The representation addresses a number of common catalog search design scenarios. In addition to catalogs of static data (e.g., different sizes of pipes), it is possible to model/search subdesigns that can provide performance data based upon operating conditions. The use of catalog hierarchies allows the search to simultaneously consider catalogs from different vendors and at different levels of detail, therefore achieving the capability of modeling solutions containing general information. The capabilities of the representation are demonstrated through an object-oriented computer implementation that uses a genetic optimization and search algorithm.

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