Advances of Soft Computing in Engineering by Zenon Waszczyszyn

By Zenon Waszczyszyn

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The Large Clear Span component enables the user to search for solutions with as large a span as is feasible, within the constraints of the design. Often clients prefer buildings with as much column-free space as possible because of the greater flexibility of such configurations. When the user opts for the Minimum Cost being significant, the system doesn’t actually optimise on real costs but features which are cost significant, these being:  Total weight per floor area (kg/m2)(Including steel, slab, deck, reinforcement, services)  Overall building height (m)  Net/gross floor area ratio The aim is to minimise the first two factors and maximise the third.

Point mutation randomly selects a gene to alter and then uses the same procedures as described during initialisation to generate a new point depending on whether a support or vertex is selected. Shuffle mutation reorders a length of the genome. This operator is included because genome ordering is important thus a solution maybe improved by shuffling the genes. 8 Fitness Function This work uses the minimisation of structural weight, enclosed volume and surface area as its major objectives. These are combined with a structural parameter that seeks to ensure constraints such as allowable buckling, tensile and compressive stresses are not violated in the structure.

This process is accomplished by constructing the genome’s convex hull, via the incremental algorithm. Once the convex hull is constructed, its edges become the structural members of the dome. , 1989). A penalty function reduces an individual’s fitness by an amount proportional to the constraint violation. It must also consider invalid structures that cannot sustain the user defined loads (because, due to the way the phenotype is constructed, there is no guarantee that they will be included in the final dome as they may not form part of the convex hull).

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Advances of Soft Computing in Engineering by Zenon Waszczyszyn
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