Optimal design of complex engineering systems is challenging because numerous design variables and constraints are present. Dynamic changes in design requirements and lack of complete knowledge of subsystem requirements add to the complexity. We propose an enhanced distributed pool architecture to aid distributed solving of design optimization problems. The approach not only saves solution time but is also resilient against failures of some processors. It is best suited to handle highly constrained design problems, with dynamically changing constraints, where finding even a feasible solution (FS) is challenging. In our work, this task is distributed among many processors. Constraints can be easily added or removed without having to restart the solution process. We demonstrate the efficacy of our method in terms of computational savings and resistance to partial failures of some processors, using two mixed integer nonlinear programming (MINLP)-class mechanical design optimization problems.
A Distributed Pool Architecture for Highly Constrained Optimization Problems in Complex Systems Design
Contributed by the Computers and Information Division of ASME for publication in the Journal of Computing and Information Science in Engineering. Manuscript received June 26, 2011; final manuscript received May 16, 2013; published online July 22, 2013. Editor: Bahram Ravani.
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Pandey, V., and Mourelatos, Z. P. (July 22, 2013). "A Distributed Pool Architecture for Highly Constrained Optimization Problems in Complex Systems Design." ASME. J. Comput. Inf. Sci. Eng. September 2013; 13(3): 031006. https://doi.org/10.1115/1.4024713
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