Nelder-Mead simplex modifications for simulation optimization
Management Science
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
Accelerating the convergence of random search methods for discrete stochastic optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
A fully sequential procedure for indifference-zone selection in simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Proceedings of the 33nd conference on Winter simulation
Pattern Search Algorithms for Mixed Variable Programming
SIAM Journal on Optimization
On the Convergence of Pattern Search Algorithms
SIAM Journal on Optimization
Pattern Search Algorithms for Bound Constrained Minimization
SIAM Journal on Optimization
Pattern Search Methods for Linearly Constrained Minimization
SIAM Journal on Optimization
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A combined procedure for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
RANK ORDERING AND POSITIVE BASES IN PATTERN SEARCH ALGORITHMS
Pattern search algorithms for mixed variable general constrained optimization problems
Pattern search algorithms for mixed variable general constrained optimization problems
Enhancing evolutionary algorithms with statistical selection procedures for simulation optimization
WSC '05 Proceedings of the 37th conference on Winter simulation
| Hi-index | 0.00 |
A new algorithm class is presented for optimization of stochastic simulation models. The algorithms, which combine generalized pattern search (GPS) with ranking and selection (R&S), require "black-box" simulation evaluations and are applicable to problems with mixed variables (continuous, discrete numeric, and categorical). Implementation of the Mixed-variable Generalized Pattern Search with Ranking and Selection (MGPS-RS) algorithm with three different R&S procedures is demonstrated and tested on a small set of standard test functions. Results of this preliminary performance evaluation are summarized and compared with existing search methods.