Research Initiation: Global Optimization Algorithms for Engineering Design

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The engineering community needs efficient algorithms for solving global optimization problems in design. Global optimization problems require minimizing a function possessing multiple local minima. A practical example is finding the optimal design of a composite laminated stiffened panel used in aircraft structures. This research has three objectives. The first is to develop a random search algorithm that includes both integer and continuous variables. A simulated annealing algorithm for mixed integer/continuous global optimization will be developed, because simulated annealing has already demonstrated some effectiveness in both the integer domain and the continuous domain. The second is to take advantage of estimates of a Lipschitz constant in the optimization algorithm. The third is to decrease an algorithm's probability of getting trapped in a local minimum that is not the global minimum. Together these objectives will improve algorithms in a manner that will make formulating and solving global optimization problems more practical and accessible to engineers. The results will be applicable to aspects of design in all engineering disciplines.