The OPTLSO Procedure

Bowman, K. O. and Shenton, L. R. (1983), “Johnson’s System of Distributions,” in S. Kotz, N. L. Johnson, and C. B. Read, eds., Encyclopedia of Statistical Sciences, volume 4, 303–314, New York: John Wiley & Sons.

Coello Coello, C. A. and Cruz Cortes, N. (2005), “Solving Multiobjective Optimization Problems Using an Artificial Immune System,” Genetic Programming and Evolvable Machines, 6, 163–190.

Custódio, A. L., Madeira, J. F. A., Vaz, A. I. F., and Vicente, L. N. (2011), “Direct Multisearch for Multiobjective Optimization,” SIAM Journal on Optimization, 21, 1109–1140.

Floudas, C. A. and Pardalos, P. M. (1992), Recent Advances in Global Optimization, Princeton, NJ: Princeton University Press.

Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Reading, MA: Addison-Wesley.

Gray, G. A. and Fowler, K. R. (2011), “The Effectiveness of Derivative-Free Hybrid Methods for Black-Box Optimization,” International Journal of Mathematical Modeling and Numerical Optimization, 2, 112–133.

Gray, G. A., Fowler, K. R., and Griffin, J. D. (2010), “Hybrid Optimization Schemes for Simulation-Based Problems,” Procedia Computer Science, 1, 1349–1357.

Gray, G. A. and Kolda, T. G. (2006), “Algorithm 856: APPSPACK 4.0: Asynchronous Parallel Pattern Search for Derivative-Free Optimization,” ACM Transactions on Mathematical Software, 32, 485–507.

Griffin, J. D., Fowler, K. R., Gray, G. A., and Hemker, T. (2011), “Derivative-Free Optimization via Evolutionary Algorithms Guiding Local Search (EAGLS) for MINLP,” Pacific Journal of Optimization, 7, 425–443.

Griffin, J. D. and Kolda, T. G. (2010a), “Asynchronous Parallel Hybrid Optimization Combining DIRECT and GSS,” Optimization Methods and Software, 25, 797–817.

Griffin, J. D. and Kolda, T. G. (2010b), “Nonlinearly Constrained Optimization Using Heuristic Penalty Methods and Asynchronous Parallel Generating Set Search,” Applied Mathematics Research Express, 2010, 36–62.

Griffin, J. D., Kolda, T. G., and Lewis, R. M. (2008), “Asynchronous Parallel Generating Set Search for Linearly Constrained Optimization,” SIAM Journal on Scientific Computing, 30, 1892–1924.

Haverly, C. A. (1978), “Studies of the Behavior of Recursion for the Pooling Problem,” SIGMAP Bulletin, Association for Computing Machinery, 25, 19–28.

Holland, J. H. (1975), Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, Ann Arbor: University of Michigan Press.

Hough, P. D., Kolda, T. G., and Patrick, H. A. (2000), Usage Manual for APPSPACK 2.0, Technical Report SAND2000-8843, Sandia National Laboratories, Albuquerque, NM and Livermore, CA.

Huband, S., Hingston, P., Barone, L., and While, L. (2006), “A Review of Multiobjective Test Problems and a Scalable Test Problem Toolkit,” IEEE Transactions on Evolutionary Computation, 10, 477–506.

Jones, D. R., Perttunen, C. D., and Stuckman, B. E. (1993), “Lipschitzian Optimization without the Lipschitz Constant,” Journal of Optimization Theory and Applications, 79, 157–181.

Kolda, T. G., Lewis, R. M., and Torczon, V. (2003), “Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods,” SIAM Review, 45, 385–482.

Liebman, J., Lasdon, L., Schrage, L., and Waren, A. (1986), Modeling and Optimization with GINO, Redwood City, CA: Scientific Press.

Michalewicz, Z. (1996), Genetic Algorithms + Data Structures = Evolution Programs, New York: Springer-Verlag.

Moré, J. J., Garbow, B. S., and Hillstrom, K. E. (1981), “Testing Unconstrained Optimization Software,” ACM Transactions on Mathematical Software, 7, 17–41.

Plantenga, T. (2009), HOPSPACK 2.0 User Manual (v 2.0.2), Technical report, Sandia National Laboratories.

Schütze, O., Esquivel, X., Lara, A., and Coello Coello, C. A. (2012), “Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization,” IEEE Transactions on Evolutionary Computation, 16, 504–522.

Taddy, M. A., Lee, H. K. H., Gray, G. A., and Griffin, J. D. (2009), “Bayesian Guided Pattern Search for Robust Local Optimization,” Technometrics, 51, 389–401.

Van Veldhuizen, D. A. (1999), Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations, Ph.D. diss., Air Force Institute of Technology.