Shubhangi G. Deshpande

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A new Pareto front approximation method is proposed for multiobjective optimization problems with bound constraints. The method employs a hybrid optimization approach using two derivative free direct search techniques, and intends to solve blackbox simulation based multiob-jective optimization problems where the analytical form of the objectives is not(More)
The process of conceptual aircraft design has advanced tremendously in the past few decades due to rapidly developing computer technology. Today's modern aerospace systems exhibit strong, interdisciplinary coupling and require a multidisciplinary, collaborative approach. Efficient transfer, sharing, and manipulation of aircraft design and analysis data in(More)
Large scale, multidisciplinary, engineering designs are always difficult due to the complexity and dimensionality of these problems. Direct coupling between the analysis codes and the optimization routines can be prohibitively time consuming due to the complexity of the underlying simulation codes. One way of tackling this problem is by constructing(More)
This paper presents a data driven, surrogate based optimization algorithm that uses a sequential approximate optimization (SAO) framework and a statistical sampling approach. The biggest concern in using the SAO framework based on statistical sampling is the generation of the required database. A data driven approach is proposed to tackle this situation,(More)
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