Lipschitzian optimization without the Lipschitz constant
Journal of Optimization Theory and Applications
Frame based methods for unconstrained optimization
Journal of Optimization Theory and Applications
Dynamic Data Structures for a Direct Search Algorithm
Computational Optimization and Applications
Proceedings of the 35th conference on Winter simulation: driving innovation
Mesh Adaptive Direct Search Algorithms for Constrained Optimization
SIAM Journal on Optimization
Design and implementation of a massively parallel version of DIRECT
Computational Optimization and Applications
Performance Modeling and Analysis of a Massively Parallel Direct - Part 1
International Journal of High Performance Computing Applications
Performance Modeling and Analysis of a Massively Parallel Direct - Part 2
International Journal of High Performance Computing Applications
Algorithm 897: VTDIRECT95: Serial and parallel codes for the global optimization algorithm direct
ACM Transactions on Mathematical Software (TOMS)
A power aware study for VTDIRECT95 using DVFS
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Lipschitz gradients for global optimization in a one-point-based partitioning scheme
Journal of Computational and Applied Mathematics
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Two parallel deterministic direct search algorithms are combined to find improved parameters for a system of differential equations designed to simulate the cell cycle of budding yeast. Comparing the model simulation results to experimental data is difficult because most of the experimental data is qualitative rather than quantitative. An algorithm to convert simulation results to mutant phenotypes is presented. Vectors of the 143 parameters defining the differential equation model are rated by a discontinuous objective function. Parallel results on a 2200 processor supercomputer are presented for a global optimization algorithm, DIRECT, a local optimization algorithm, MADS, and a hybrid of the two.