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Rule Based Stochastic Tree SearchMukund Kumar, for M.S.E.The University of Texas at Austin, 2011 Supervisor: Matthew I Campbell This work presents an enhancement of a search process that is suited for a problem that can be solved using a graph grammar based generative tree. Generative grammar can be used to generate a vast number of design alternatives by using a seed graph of the problem and a set of transformation rules. The problem is to find the best solution among this space by doing the least number of evaluations possible. In a previous paper, an interactive algorithm for searching in a graph grammar representation was presented. The process was demonstrated for a problem of tying a necktie and the work here builds on top of this process to be useful for solving engineering problem. To test the search process, two problems, a photovoltaic array topology optimization problem and an electromechanical product redesign problem, are chosen. It is shown this search process converges in finding the best solution within a few hundred evaluations which is a manageable number compared to the large solution space of millions of candidates. Further optimization and tweaks are done on the process to control exploration vs. exploitation and find the parameters for fastest convergence and the best solution.v

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