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We investigate the design of control algorithms for puck clus- tering simulations. Of interest is the control of the variance in puck cluster sizes, particularly when multiple clusters are being created. We present a theoretical framework under which behaviors may be designed which serve to control puck cluster sizes.
In genetic search algorithms and optimization routines, the representation of the mutation and crossover operators are typically defaulted to the canonical basis. We show that this can be influential in the usefulness of the search algorithm. We then pose the question of how to find a basis for which the search algorithm is most useful. The conjugate schema… (More)
In this paper we design swarm clustering algorithm to build, move and place clusters of building materials on the desired place on ¢ ¡ plane. Such algorithm consists of three phases: building clusters, moving them radially and then orbitally. We present an example that demonstrates desired cluster placement. In particular, it is shown that with proposed… (More)