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Journal of the ACM (JACM)
Direct search methods: then and now
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Asynchronous Parallel Pattern Search for Nonlinear Optimization
SIAM Journal on Scientific Computing
On the Global Convergence of Derivative-Free Methods for Unconstrained Optimization
SIAM Journal on Optimization
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
On the Convergence of Asynchronous Parallel Pattern Search
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Optimizing an Empirical Scoring Function for Transmembrane Protein Structure Determination
INFORMS Journal on Computing
Optimizing an Empirical Scoring Function for Transmembrane Protein Structure Determination
INFORMS Journal on Computing
A DFO technique to calibrate queueing models
Computers and Operations Research
Leveraging efficient parallel pattern search for clock mesh optimization
Proceedings of the 2009 International Conference on Computer-Aided Design
High-level approach to modeling of observed system behavior
Performance Evaluation
Tradeoff analysis and optimization of power delivery networks with on-chip voltage regulation
Proceedings of the 47th Design Automation Conference
Algorithm 909: NOMAD: Nonlinear Optimization with the MADS Algorithm
ACM Transactions on Mathematical Software (TOMS)
FEM based 3D tumor growth prediction for kidney tumor
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
A Derivative-Free Algorithm for Least-Squares Minimization
SIAM Journal on Optimization
A parallel, asynchronous method for derivative-free nonlinear programs
ICMS'06 Proceedings of the Second international conference on Mathematical Software
Design analysis of IC power delivery
Proceedings of the International Conference on Computer-Aided Design
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Simultaneous optimization and uncertainty quantification
Journal of Computational Methods in Sciences and Engineering - Special issue on Advances in Simulation-Driven Optimization and Modeling
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APPSPACK is software for solving unconstrained and bound-constrained optimization problems. It implements an asynchronous parallel pattern search method that has been specifically designed for problems characterized by expensive function evaluations. Using APPSPACK to solve optimization problems has several advantages: No derivative information is needed; the procedure for evaluating the objective function can be executed via a separate program or script; the code can be run serially or in parallel, regardless of whether the function evaluation itself is parallel; and the software is freely available. We describe the underlying algorithm, data structures, and features of APPSPACK version 4.0, as well as how to use and customize the software.