How to use initialize method of Knapsack Package

Best Knapsack_ruby code snippet using Knapsack.initialize

knapsack3.rb

Source:knapsack3.rb Github

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...33 new(chromosome)34 end35 attr_accessor :score, :fitness36 attr_reader :chromosome37 def initialize(chromosome = nil, chromosome_size = nil)38 if chromosome39 @chromosome = chromosome40 else41 @chromosome = []42 chromosome_size.times { @chromosome << (rand(0..1) == 1) }43 end44 end45 private_class_method :new46 def chromosome_as_list47 list = []48 @chromosome.each_with_index do |gene, index|49 list << Knapsack::ITEMS[index].name if gene50 end51 list.join(', ')52 end53 def >(other)54 return true if other.nil?55 score > other.score56 end57end58class Population < Array59 def initialize(chromosome_size, population_size)60 population_size.times { self << Individual.random(chromosome_size) }61 end62 def best63 self.sort_by{|individual| individual.score}.last64 end65end66class Evaluator67 def initialize(capacity, population)68 @capacity = capacity69 @population = population70 end71 def evaluate72 @population.each {|individual| score(individual) }73 fitness74 end75 private76 def score(individual)77 value = 078 weight = 079 individual.chromosome.each_with_index do |item, index|80 if item81 value += Knapsack::ITEMS[index].value82 weight += Knapsack::ITEMS[index].weight83 end84 end85 if weight > @capacity86 value -= 2 * (weight - @capacity)87 value = 0 if value < 088 end89 individual.score = value90 end91 def fitness92 total = @population.inject(0) {|sum, individual| sum + individual.score }93 size = @population.size94 @population.each do |individual|95 individual.fitness = individual.score.to_f / total * size96 end97 end98end99class GeneticAlgorithm100 def initialize(generations, population, capacity, mutation_rate)101 @generations = generations102 @population = population103 @capacity = capacity104 @mutation_rate = mutation_rate105 @crossover = Crossover.new(Knapsack::ITEMS.size, mutation_rate)106 end107 def run108 best_ever = nil109 @generations.times do |generation|110 Evaluator.new(@capacity, @population).evaluate111 best = @population.best112 best_ever = best if best > best_ever113 display(generation, best_ever)114 next_generation115 end116 display_best_ever(best_ever)117 end118 private119 def display(generation, individual)120 puts "Gen: #{generation} Best score: #{individual.score}"121 end122 def display_best_ever(individual)123 puts "----------------------"124 puts "Best ever"125 puts "----------------------"126 puts "score: #{individual.score}"127 puts "chromosome: #{individual.chromosome_as_list}"128 end129 def next_generation130 @population.sort_by! {|i| i.score}131 elite = @population.pop(4)132 pool = MatingPool.new(@population)133 population_size = @population.size134 @population.clear135 population_size.times do136 @population << @crossover.two_point(pool.random, pool.random)137 end138 @population.concat elite139 end140end141class MatingPool142 def initialize(population)143 @mating_pool = []144 population.each do |individual|145 integer_part = individual.fitness.to_i146 real_part = individual.fitness - integer_part147 integer_part.times { @mating_pool << individual.dup }148 @mating_pool << individual.dup if rand < real_part149 end150 @size = @mating_pool.size151 end152 def random153 @mating_pool[rand(@size)]154 end155end156class Crossover157 def initialize(chromosome_size, mutation_rate)158 @size = chromosome_size159 @rate = mutation_rate160 @mutator = Mutator.new(@size, @rate)161 end162 def two_point(parent1, parent2)163 child = assemble(parent1, parent2, two_cut_points)164 child = @mutator.mutate(child)165 Individual.from_chromosome(child)166 end167 private168 def two_cut_points169 point1 = cut_point170 point2 = cut_point171 point1, point2 = point2, point1 if point1 > point2172 [point1, point2]173 end174 def cut_point175 rand(@size)176 end177 def assemble(parent1, parent2, points)178 point1, point2 = points179 parent1.chromosome[0...point1] + parent2.chromosome[point1..point2] +180 parent1.chromosome[point2+1..-1]181 end182end183class Mutator184 def initialize(chromosome_size, mutation_rate)185 @size = chromosome_size186 @rate = mutation_rate187 end188 def mutate(chromosome)189 @size.times do |index|190 if rand < @rate191 chromosome[index] = ! chromosome[index]192 end193 end194 chromosome195 end196end197knapsack_capacity = 400198generations = 100...

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knapsack2.rb

Source:knapsack2.rb Github

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...33 new(chromosome)34 end35 attr_accessor :score, :fitness36 attr_reader :chromosome37 def initialize(chromosome = nil, chromosome_size = nil)38 if chromosome39 @chromosome = chromosome40 else41 @chromosome = []42 chromosome_size.times { @chromosome << (rand(0..1) == 1) }43 end44 end45 private_class_method :new46 def chromosome_as_list47 list = []48 @chromosome.each_with_index do |gene, index|49 list << Knapsack::ITEMS[index].name if gene50 end51 list.join(', ')52 end53 def >(other)54 return true if other.nil?55 score > other.score56 end57end58class Population < Array59 def initialize(chromosome_size, population_size)60 population_size.times { self << Individual.random(chromosome_size) }61 end62 def best63 self.sort_by{|individual| individual.score}.last64 end65end66class Evaluator67 def initialize(capacity, population)68 @capacity = capacity69 @population = population70 end71 def evaluate72 @population.each {|individual| score(individual) }73 fitness74 end75 private76 def score(individual)77 value = 078 weight = 079 individual.chromosome.each_with_index do |item, index|80 if item81 value += Knapsack::ITEMS[index].value82 weight += Knapsack::ITEMS[index].weight83 end84 end85 if weight > @capacity86 individual.score = 087 else88 individual.score = value89 end90 end91 def fitness92 total = @population.inject(0) {|sum, individual| sum + individual.score }93 size = @population.size94 @population.each do |individual|95 individual.fitness = individual.score.to_f / total * size96 end97 end98end99class GeneticAlgorithm100 def initialize(generations, population, capacity, mutation_rate)101 @generations = generations102 @population = population103 @capacity = capacity104 @mutation_rate = mutation_rate105 @crossover = Crossover.new(Knapsack::ITEMS.size, mutation_rate)106 end107 def run108 best_ever = nil109 @generations.times do |generation|110 Evaluator.new(@capacity, @population).evaluate111 best = @population.best112 best_ever = best if best > best_ever113 display(generation, best)114 next_generation115 end116 display_best_ever(best_ever)117 end118 private119 def display(generation, individual)120 puts "Gen: #{generation} Best score: #{individual.score}"121 end122 def display_best_ever(individual)123 puts "----------------------"124 puts "Best ever"125 puts "----------------------"126 puts "score: #{individual.score}"127 puts "chromosome: #{individual.chromosome_as_list}"128 end129 def next_generation130 @population.sort_by! {|i| i.score}131 elite = @population.pop(4)132 pool = MatingPool.new(@population)133 population_size = @population.size134 @population.clear135 population_size.times do136 @population << @crossover.two_point(pool.random, pool.random)137 end138 @population.concat elite139 end140end141class MatingPool142 def initialize(population)143 @mating_pool = []144 population.each do |individual|145 integer_part = individual.fitness.to_i146 real_part = individual.fitness - integer_part147 integer_part.times { @mating_pool << individual.dup }148 @mating_pool << individual.dup if rand < real_part149 end150 @size = @mating_pool.size151 end152 def random153 @mating_pool[rand(@size)]154 end155end156class Crossover157 def initialize(chromosome_size, mutation_rate)158 @size = chromosome_size159 @rate = mutation_rate160 @mutator = Mutator.new(@size, @rate)161 end162 def two_point(parent1, parent2)163 child = assemble(parent1, parent2, two_cut_points)164 child = @mutator.mutate(child)165 Individual.from_chromosome(child)166 end167 private168 def two_cut_points169 point1 = cut_point170 point2 = cut_point171 point1, point2 = point2, point1 if point1 > point2172 [point1, point2]173 end174 def cut_point175 rand(@size)176 end177 def assemble(parent1, parent2, points)178 point1, point2 = points179 parent1.chromosome[0...point1] + parent2.chromosome[point1..point2] +180 parent1.chromosome[point2+1..-1]181 end182end183class Mutator184 def initialize(chromosome_size, mutation_rate)185 @size = chromosome_size186 @rate = mutation_rate187 end188 def mutate(chromosome)189 @size.times do |index|190 chromosome[index] = ! chromosome[index] if rand < @rate191 end192 chromosome193 end194end195knapsack_capacity = 400196generations = 100197population = Population.new(Knapsack::ITEMS.size, 1000)198mutation = 0.01...

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knapsack.rb

Source:knapsack.rb Github

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...33 new(chromosome)34 end35 attr_accessor :score, :fitness36 attr_reader :chromosome37 def initialize(chromosome = nil, chromosome_size = nil)38 if chromosome39 @chromosome = chromosome40 else41 @chromosome = []42 chromosome_size.times { @chromosome << (rand(0..1) == 1) }43 end44 end45 private_class_method :new46 def chromosome_as_list47 list = []48 @chromosome.each_with_index do |gene, index|49 list << Knapsack::ITEMS[index].name if gene50 end51 list.join(', ')52 end53 def >(other)54 return true if other.nil?55 score > other.score56 end57end58class Population < Array59 def initialize(chromosome_size, population_size)60 population_size.times { self << Individual.random(chromosome_size) }61 end62 def best63 self.sort_by{|individual| individual.score}.last64 end65end66class Evaluator67 def initialize(capacity, population)68 @capacity = capacity69 @population = population70 end71 def evaluate72 @population.each {|individual| score(individual) }73 fitness74 end75 private76 def score(individual)77 value = 078 weight = 079 individual.chromosome.each_with_index do |item, index|80 if item81 value += Knapsack::ITEMS[index].value82 weight += Knapsack::ITEMS[index].weight83 end84 end85 if weight > @capacity86 individual.score = 087 else88 individual.score = value89 end90 end91 def fitness92 total = @population.inject(0) {|sum, individual| sum + individual.score }93 size = @population.size94 @population.each do |individual|95 individual.fitness = individual.score.to_f / total * size96 end97 end98end99class GeneticAlgorithm100 def initialize(generations, population, capacity, mutation_rate)101 @generations = generations102 @population = population103 @capacity = capacity104 @mutation_rate = mutation_rate105 @crossover = Crossover.new(Knapsack::ITEMS.size, mutation_rate)106 end107 def run108 best_ever = nil109 @generations.times do |generation|110 Evaluator.new(@capacity, @population).evaluate111 best = @population.best112 best_ever = best if best > best_ever113 display(generation, best)114 next_generation115 end116 display_best_ever(best_ever)117 end118 private119 def display(generation, individual)120 puts "Gen: #{generation} Best score: #{individual.score}"121 end122 def display_best_ever(individual)123 puts "----------------------"124 puts "Best ever"125 puts "----------------------"126 puts "score: #{individual.score}"127 puts "chromosome: #{individual.chromosome_as_list}"128 end129 def next_generation130 pool = MatingPool.new(@population)131 population_size = @population.size132 @population.clear133 population_size.times do134 @population << @crossover.two_point(pool.random, pool.random)135 end136 end137end138class MatingPool139 def initialize(population)140 @mating_pool = []141 population.each do |individual|142 integer_part = individual.fitness.to_i143 real_part = individual.fitness - integer_part144 integer_part.times { @mating_pool << individual.dup }145 @mating_pool << individual.dup if rand < real_part146 end147 @size = @mating_pool.size148 end149 def random150 @mating_pool[rand(@size)]151 end152end153class Crossover154 def initialize(chromosome_size, mutation_rate)155 @size = chromosome_size156 @rate = mutation_rate157 @mutator = Mutator.new(@size, @rate)158 end159 def two_point(parent1, parent2)160 child = assemble(parent1, parent2, two_cut_points)161 child = @mutator.mutate(child)162 Individual.from_chromosome(child)163 end164 private165 def two_cut_points166 point1 = cut_point167 point2 = cut_point168 point1, point2 = point2, point1 if point1 > point2169 [point1, point2]170 end171 def cut_point172 rand(@size)173 end174 def assemble(parent1, parent2, points)175 point1, point2 = points176 parent1.chromosome[0...point1] + parent2.chromosome[point1..point2] +177 parent1.chromosome[point2+1..-1]178 end179end180class Mutator181 def initialize(chromosome_size, mutation_rate)182 @size = chromosome_size183 @rate = mutation_rate184 end185 def mutate(chromosome)186 @size.times do |index|187 chromosome[index] = ! chromosome[index] if rand < @rate188 end189 chromosome190 end191end192knapsack_capacity = 400193generations = 100194population = Population.new(Knapsack::ITEMS.size, 1000)195mutation = 0.01...

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initialize

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1knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])2knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])3knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])4knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])5knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])6knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])7knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])8knapsack = Knapsack.new(5, [1,2,3,4,5], [5,4,3,2,1])9knapsack = Knapsack.new(5, [1,2,3,

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initialize

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1k = Knapsack.new(50, 6)2k.load_items("items.txt")3k = Knapsack.new(50, 6)4k.load_items("items.txt")5k = Knapsack.new(50, 6)6k.load_items("items.txt")7k = Knapsack.new(50, 6)8k.load_items("items.txt")9k = Knapsack.new(50, 6)10k.load_items("items.txt")11k = Knapsack.new(50, 6)12k.load_items("items.txt")13k = Knapsack.new(50, 6)14k.load_items("items.txt")15k = Knapsack.new(50, 6)16k.load_items("items.txt")17k = Knapsack.new(50, 6)18k.load_items("items.txt")19k = Knapsack.new(50, 6)20k.load_items("items.txt")21k = Knapsack.new(50, 6)22k.load_items("items.txt")

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initialize

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1knapsack = Knapsack.new(100, 100, 100)2knapsack = Knapsack.new(100, 100, 100)3knapsack = Knapsack.new(100, 100, 100)4knapsack = Knapsack.new(100, 100, 100)5knapsack = Knapsack.new(100, 100, 100)

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initialize

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1 def initialize(capacity)2 def initialize(name)3 def initialize(name)4 def initialize(name)5 def initialize(name)

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initialize

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1k = Knapsack.new(50, 6)2k.load_items("items.txt")3k = Knapsack.new(50, 6)4k.load_items("items.txt")5k = Knapsack.new(50, 6)6k.load_items("items.txt")7k = Knapsack.new(50, 6)8k.load_items("items.txt")9k = Knapsack.new(50, 6)10k.load_items("items.txt")11k = Knapsack.new(50, 6)12k.load_items("items.txt")13k = Knapsack.new(50, 6)14k.load_items("items.txt")15k = Knapsack.new(50, 6)16k.load_items("items.txt")17k = Knapsack.new(50, 6)18k.load_items("items.txt")19k = Knapsack.new(50, 6)20k.load_items("items.txt")21k = Knapsack.new(50, 6)22k.load_items("items.txt")

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initialize

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1knapsack = Knapsack.new(100, 100, 100)2knapsack = Knapsack.new(100, 100, 100)3knapsack = Knapsack.new(100, 100, 100)4knapsack = Knapsack.new(100, 100, 100)5knapsack = Knapsack.new(100, 100, 100)

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initialize

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1 def initialize(capacity)2 def initialize(name)3 def initialize(name)4 def initialize(name)5 def initialize(name)

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initialize

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1k = Knapsack.new(50, 6)2k.load_items("items.txt")3k = Knapsack.new(50, 6)4k.load_items("items.txt")5k = Knapsack.new(50, 6)6k.load_items("items.txt")7k = Knapsack.new(50, 6)8k.load_items("items.txt")9k = Knapsack.new(50, 6)10k.load_items("items.txt")11k = Knapsack.new(50, 6)12k.load_items("items.txt")13k = Knapsack.new(50, 6)14k.load_items("items.txt")15k = Knapsack.new(50, 6)16k.load_items("items.txt")17k = Knapsack.new(50, 6)18k.load_items("items.txt")19k = Knapsack.new(50, 6)20k.load_items("items.txt")21k = Knapsack.new(50, 6)22k.load_items("items.txt")

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initialize

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1knapsack = Knapsack.new(100, 100, 100)2knapsack = Knapsack.new(100, 100, 100)3knapsack = Knapsack.new(100, 100, 100)4knapsack = Knapsack.new(100, 100, 100)5knapsack = Knapsack.new(100, 100, 100)

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initialize

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1 def initialize(capacity)2 def initialize(name)3 def initialize(name)4 def initialize(name)5 def initialize(name)

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