| Type: | Package | 
| Title: | Recursive Modified Pattern Search on Hyper-Rectangle | 
| Version: | 1.1.1 | 
| Depends: | R (≥ 3.5.0) | 
| Imports: | Rcpp | 
| Collate: | 'imports.R' 'RcppExports.R' 'RMPSolveH.R' 'RMPSH-package.R' | 
| Maintainer: | Priyam Das <pdas@ncsu.edu> | 
| Description: | Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular Parameter Space. It uses a Variation of Pattern Search Technique. Described in the paper : Das (2016) <doi:10.48550/arXiv.1604.08616> . | 
| License: | GPL-3 | 
| NeedsCompilation: | yes | 
| Encoding: | UTF-8 | 
| LazyData: | true | 
| LinkingTo: | Rcpp | 
| RoxygenNote: | 7.1.0 | 
| Packaged: | 2020-06-25 21:57:13 UTC; Debsurya | 
| Author: | Priyam Das [cre, aut], Debsurya De [aut] | 
| Repository: | CRAN | 
| Date/Publication: | 2020-06-26 14:20:03 UTC | 
RMPSH: Recursive Modified Pattern Search on Hyper-Rectangle
Description
Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular Parameter Space. It uses a Variation of Pattern Search Technique. Described in the paper : Das (2016) <arXiv:1604.08616> .
Author(s)
Maintainer: Priyam Das pdas@ncsu.edu
Authors:
- Debsurya De debsurya001@gmail.com 
Recursive Modified Direct Search on Hyper-rectangle
Description
'RMPSolveH' can be Used to Minimize any Non-Convex Blackbox Function where Each Parameter has an Upper Bound and Lower Bound.
Usage
RMPSolveH(
  x0,
  func,
  lb,
  ub,
  rho_1 = 2,
  rho_2 = 2,
  phi = 1e-06,
  no_runs = 1000,
  max_iter = 10000,
  s_init = 2,
  tol_fun = 1e-06,
  tol_fun_2 = 1e-20,
  max_time = 36000,
  print_output = FALSE
)
Arguments
| x0 | Vector of Initial Guess provided by User. | 
| func | The Function to be Optimized, should be provided by the User. | 
| lb | Vector of Lower Bounds, of same Dimension as 'x0'. | 
| ub | Vector of Upper Bound, of same Dimension as 'x0' | 
| rho_1 | 'Step Decay Rate' for the First Run Only (Default is 2). | 
| rho_2 | 'Step Decay Rate' for Second Run Onwards (Default is 2). | 
| phi | Lower Bound for 'Global Step Size'. Default value is  | 
| no_runs | Max Number of 'Runs'. Default Value is 1000. | 
| max_iter | Max Number of Iterations in each 'Run'. Default Value is 10000. | 
| s_init | Initial 'Global Step Size'. Default Value is 2. It must be set Less than or Equal to 2. | 
| tol_fun | Termination Tolerance on when to decrease the 'Global Step Size'. Default Value is  | 
| tol_fun_2 | Termination Tolerance on the Difference of Norms of solution points in two Consecutive Runs. Default Value is  | 
| max_time | Time Alloted (In Seconds) for Execution of RMPSH. Default is 36000 secs (10 Hours). | 
| print_output | Binary Command to Print Optimized Value of Objective Function after Each Iteration. Default is set as FALSE. | 
Value
The Optimal Solution Point.
References
- Das, Priyam 
 "Black-box optimization on hyper-rectangle using Recursive Modified Pattern Search and application to ROC-based Classification Problem"
 (available at 'arXiv http://arxiv.org/abs/1604.08616).
Examples
g <- function(y)
 return(-20 * exp(-0.2 * sqrt(0.5 * (y[1] ^ 2 + y[2] ^ 2))) -
 exp(0.5 * (cos(2 * pi * y[1]) + cos(2 * pi * y[2]))) + exp(1) + 20)
starting_point <- rep(1, 10)
g(starting_point)
solution <- RMPSolveH(starting_point, g, rep(-33, 10), rep(33, 10))
g(solution)
RMPSolveH(c(2, 4, 6, 2, 1), g, rep(-3, 5), rep(23, 5), print_output = TRUE)
# Will Print the Updates after Each Iteration
g <- function(y)
 return(sum(y ^ 2))
RMPSolveH(rep(2.3, 100),
          g,
          rep(-11, 100),
          rep(13, 100),
          max_time = 2,
          print = 1)
# Will Exit and Return Result after 2 Seconds