Module CuckooSearch

! Modern Fortran implementation of Cuckoo Search Optimizers. The first
! version of CS implemented is the modified Cuckoo Search algorithm 
! written by Sean Walton at Swansea University and described in:
! S.Walton, O.Hassan, K.Morgan and M.R.Brown "Modified cuckoo search: A
! new gradient free optimisation algorithm" Chaos, Solitons & Fractals Vol
! 44 Issue 9, Sept 2011 pp. 710-718 DOI:10.1016/j.chaos.2011.06.004

! MCS is based on Version 3 of Walton's MATLAB code which can be found at:
! https://code.google.com/archive/p/modified-cs/

! Note that Walton's MATLAB code unfortunately is covered by the GPL2 license
! and as a derived work that license extends to this code

! Original license

! This program is free software: you can redistribute it and/or modify
! it under the terms of the GNU General Public License as published by
! the Free Software Foundation, version 2.
! 
! This program is distributed in the hope that it will be useful,
! but WITHOUT ANY WARRANTY; without even the implied warranty of
! MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
! GNU General Public License for more details.
! 
! You should have received a copy of the GNU General Public License
! along with this program.  If not, see <http://www.gnu.org/licenses/>.

! Other versions of CS will be added as time permits

! Written by: Dr. Richard Weed
!             Center for Advanced Vehicular Systems
!             Mississippi State University
!             Miss. State, MS 39762

  USE objectiveFunctions
  USE optimizerClass

  Implicit NONE

  Type, Extends(optimizer_t) :: mcs_t ! define a class for the modified Cuckoo Search

    Integer(IK)                   :: numDesVars         = 1   
    Integer(IK)                   :: numTotalGens       = 100
    Integer(IK)                   :: numNestI           = 100
    Integer(IK)                   :: numDeletedEggs     = 1
    Integer(IK)                   :: minNests           = 10
    Integer(C_ENUM)               :: flightType         = YangDeb_Levy 
    Real(RK)                      :: pa                 = 0.7_RK
    Real(RK)                      :: pwr                = 0.5_RK
    Real(RK)                      :: MaxLevyStepFactor  = 100._RK
    Logical                       :: constrainSearch    = .TRUE.
    Real(RK),         ALLOCATABLE :: optDesVals(:)
    Real(RK),         ALLOCATABLE :: NestsI(:,:)
    Real(RK),         ALLOCATABLE :: bounds(:,:)
    
       
  Contains

    Procedure :: deallocMCS
    Procedure :: allocMCSNestsBounds
    Procedure :: initMCSParams
    Procedure :: MCSinitNestsUser
    Procedure :: MCSinitNestsRandom
    Procedure :: MCSoptimizer

    Generic   :: initNests   => MCSinitNestsUser, MCSinitNestsRandom
    Generic   :: optimizer   => MCSoptimizer
    Generic   :: dealloc     => deallocMCS
    Generic   :: allocNests  => allocMCSNestsBounds
    Generic   :: init        => initMCSparams
      
  End Type

Contains

  Subroutine MCSoptimizer(this, objFun)

! Objective Function can be any extension of class objective_function_t 
! which requires you to define a wrapper around your actual function
! Optionally, I could have required users to pass a procedure pointer
! but I try to avoid pointers in general as much as possible
 
    Implicit NONE

    Class(mcs_t),                Intent(INOUT) :: this
    Class(objective_function_t), Intent(INOUT) :: objFun

! rest of code here

  End Subroutine MCSoptimizer

End Module CuckooSearch