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Algorithm 856: APPSPACK 4.0: asynchronous parallel pattern search for derivative-free optimization
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Source ACM Transactions on Mathematical Software (TOMS) archive
Volume 32 ,  Issue 3  (September 2006) table of contents
Pages: 485 - 507  
Year of Publication: 2006
ISSN:0098-3500
Authors
Genetha A. Gray  Sandia National Laboratories, Livermore, CA
Tamara G. Kolda  Sandia National Laboratories, Livermore, CA
Publisher
ACM  New York, NY, USA
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Software for "APPSPACK 4.0: asynchronous parallel pattern search for derivative-free optimization"


ABSTRACT

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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Chiesa, M. L., Jones, R. E., Perano, K. J., and Kolda, T. G. 2004. Parallel optimization of forging proceeses for optimal material properties. Tech. Rep., Sandia National Laboratories.
 
2
Choi, T. D., Eslinger, O. J., Gilmore, P., Kelley, C. T., and Gablonsky, J. M. 1999. IFFCO: Implicit filtering for constrained optimization, version 2. Tech. Rep. CRSC-TR99-23, Center for Research in Scientific Computing, North Carolina State University.
 
3
Croue, G. 2003. Optimisation par la méthode APPS d'un problème de propagation d'interfaces (in French). M.S. thesis, Ecole Centrale de Lyon, France.
 
4
Dolan, E. D., Fourer, R., Moré, J. J., and Munson, T. J. 2002. The NEOS server for optimization: Version 4 and beyond. Tech. Rep. MCS-TM-250, Argonne National Laboratory.
 
5
Fowler, K. R., Reese, J. P., Kees, C. E., J. E. Dennis, D., Kelley, C. T., Miller, C. T., Audet, C., Booker, A. J., Couture, G., Darwin, R. W., Farthing, M. W., Finkel, D. E., Gablonsky, J. M., Gray, G., and Kolda, T. G. 2004. A comparison of optimization methods for problems involving flow and transport phenomena in saturated subsurface systems. In preparation.
 
6
Gilmore, P. and Kelley, C. T. 1995. An implicit filtering algorithm for optimization of functions with many local minima. SIAM J. Optimization 5, 269--285.
 
7
Gray, G. A., Kolda, T. G., Sale, K. L., and Young, M. M. 2004. Optimizing an empirical scoring function for transmembrane protein structure determination. INFORMS J. Comp. 16, 4, 406--418. Special Issue on Computational Biology.
 
8
 
9
Gropp, W. D. and Lusk, E. 1996. User's guide for mpich, a portable implementation of MPI. Tech. Rep. ANL-96/6, Mathematics and Computer Science Division, Argonne National Laboratory.
 
10
Hough, P. D., Kolda, T. G., and Patrick, H. A. 2000. Usage manual for appspack version 2.0. Tech. Rep. SAND2000-8843, Sandia National Laboratories.
 
11
 
12
Kelley, C. T. 1999. Iterative Methods for Optimization. Frontiers in Applied Mathematics, no. 18. SIAM, Philadelphia, PA.
 
13
Kolda, T. G. 2004. Revisiting asynchronous parallel pattern search. Tech. Rep. SAND2004-8055, Sandia National Laboratories, Livermore, CA 94551. February.
 
14
Kolda, T. G., Lewis, R. M., and Torczon, V. 2003. Optimization by direct search: New perspectives on some classical and modern methods. SIAM Rev. 45, 3, 385--482.
 
15
Kolda, T. G. and Torczon, V. J. 2003. Understanding asynchronous parallel pattern search. In High Performance Algorithms and Software for Nonlinear Optimization, G. Di Pillo and A. Murli, Eds. Applied Optimization, vol. 82. Kluwer Academic, Boston, 316--335.
 
16
 
17
Kupinksi, M. A., Clarkson, E., Hoppin, J. W., Chen, L., and Barrett, H. H. 2003. Experimental determination of object statistics from noisy images. J. Opt. Soc. Am. A 20, 3 (Mar.), 421--429.
 
18
 
19
 
20
Liang, J. and Chen, Y.-Q. 2003. Optimization of a fed-batch fermentation process control competition problem using the NEOS server. Proceedings of the I MECH E Part I Journal of Systems and Control Engineering 20, 3 (Mar.), 421--429.
 
21
 
22
Mathew, G., Petzold, L., and Serban, R. 2002. Computational techniques for quantification and optimization of mixing in microfluidic devices. http://www.engineering.ucsb.edu/~cse/Files/MixPaper.pdf.
 
23
McDonald, M. G. and Harbaugh, A. W. 1988. A modular three-dimensional finite-difference groundwater flow model. U.S. Geological Survey Techniques of Water Resources Investigations.
24
 
25
Torczon, V. 1995. Pattern search methods for nonlinear optimization. SIAG/OPT Views and News: A Forum for the SIAM Activity Group on Optimization 6, 7--11.
 
26
Wright, M. H. 1996. Direct search methods: Once scorned, now respectable. In Numerical Analysis 1995 (Proceedings of the 1995 Dundee Biennial Conference in Numerical Analysis), D. F. Griffiths and G. A. Watson, Eds. Pitman Research Notes in Mathematics, vol. 344. CRC Press, Boca Raton, FL, 191--208.
 
27
Yu, W. 1979. Positive basis and a class of direct search techniques. Scientia Sinica Special Issue of Mathematics, 1, 53--67.


Collaborative Colleagues:
Genetha A. Gray: colleagues
Tamara G. Kolda: colleagues