gusucode.com > 十大算法matlab程序说明 > 十大算法matlab程序说明/遗传退火法/一个Matlab的模拟退火算法工具箱/TinitT0.m
function [T0,W,Ew,Wbsf,Ebsf,Ea,Ev,steps] = TinitT0(r, walkers, newstate, X, cost, moveclass) % Fixed temperature initialization method supplied with SA Tools. % Copyright (c) 2002, by Richard Frost and Frost Concepts. % See http://www.frostconcepts.com/software for information on SA Tools. % % [T0,W,Ew,Wbsf,Ebsf,Ev,steps] = TinitT0(r, walkers, newstate, X, cost, moveclass) ; % % INPUTS: % r = initial temperature T0 % walkers = number of walkers. Must be positive integer. % newstate = (handle to) user-defined method % W0 = newstate(X) where % X = user-defined problem domain or other data, % behaviorally static. % W0 = an initial user-defined state. % X = user-defined problem domain or other data, behaviorally static. % cost = (handle to) user-defined objective method (function) % Ew = cost(X,W) where % X = user-defined problem domain or other data. % W = a user-defined state from 'newstate' or 'moveclass'. % moveclass = (handle to) user-defined method, % W = moveclass(X,W,Ea,T) where % X = user-defined problem domain or other data. % W = a user-defined state from 'newstate' or 'moveclass'. % Ea = average energy at current temperature. % T = current temperature (will be infinite in Tinit) % OUTPUTS: % T0 = initial temperature % W = user-defined state(s) from 'newstate' or 'moveclass'. % Ew = current energies corresponding to W (size walkers) % Wbsf = array of best-so-far states of size 'walkers' % Ebsf = array of best-so-far energies % Ea = average energy % Ev = energy (cost) history at T % i = arbitrary index % Ev(i,1) = step # % Ev(i,2) = walker # % Ev(i,3) = an energy visited during T % Ev(i,4) = energy attempted from Ev(i,1:3) during T % steps = # of steps taken by each walker during Tinit % % Sets T0 to the user supplied value. Calls ensembleInit(...). % [W,Ew,Wbsf,Ebsf,Ea] = ensembleInit(walkers, newstate, X, cost) ; T0 = r ; Ev = [] ; steps = 0 ;