class MHL::RechenbergController
Constants
- DEFAULT_THRESHOLD
- P_M_MAX
- P_M_MIN
- TAU
Attributes
generations[R]
threshold[R]
Public Class Methods
new(generations=5, threshold=DEFAULT_THRESHOLD, logger=nil)
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# File lib/mhl/rechenberg_controller.rb, line 11 def initialize(generations=5, threshold=DEFAULT_THRESHOLD, logger=nil) unless threshold > 0.0 and threshold < 1.0 raise ArgumentError, "The threshold parameter must be in the (0.0,1.0) range!" end @generations = generations @threshold = threshold @logger = logger @history = [] end
Public Instance Methods
call(solver, best)
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# File lib/mhl/rechenberg_controller.rb, line 21 def call(solver, best) @history << best if @history.size > @generations # calculate improvement ratio res = @history.each_cons(2).inject(0) {|s,x| s += 1 if x[1][:fitness] > x[0][:fitness]; s } / (@history.size - 1).to_f if res > @threshold # we had enough improvements - decrease impact of mutation # increase mutation probability by 5% or to P_M_MAX old_p_m = solver.mutation_probability new_p_m = [ old_p_m * TAU, P_M_MAX ].min @logger.info "increasing mutation_probability from #{old_p_m} to #{new_p_m}" if @logger solver.mutation_probability = new_p_m else # we didn't have enough improvements - increase impact of mutation # decrease mutation probability by 5% or to P_M_MAX old_p_m = solver.mutation_probability new_p_m = [ old_p_m / TAU, P_M_MIN ].max @logger.info "decreasing mutation_probability from #{old_p_m} to #{new_p_m}" if @logger solver.mutation_probability = new_p_m end # reset @history.shift(@history.size-1) end end