Improved Interactive Genetic Algorithm for Three-Dimensional Vase Modeling Design

Algorithm 1

Details of algorithm steps.

(i)	Input: population_size, crossover_rate, mutation_rate, interactive_generation, termination_generation
	Output: none
	(1) generation = 0
	(2) population[generation] = initialize_population(population_size)
	(3) model = KDT.build(DB.dataset())
	(4) While generation<=termination_generation do
	(5) model.prediction(population[generation])
	(6) If generation > interactive_generation && is_adjust() then
	(7) adjust(population[generation])
	(8) end If
	(9) evaluate(population[generation])
	(10) DB.save(population[generation])
	(11) chromosomes = encode(population[generation])
	(12) While(population[generation+1].size() < population_size) do
	(13) pairs = select(chromosomes)
	(14) If rand() < crossover_rate then
	(15) pairs = crossover(pairs)
	(16) end If
	(17) If rand() < mutation_rate then
	(18) pairs = mutate(pairs)
	(19) end If
	(20) population[generation+1].add(decode(pairs.first))
	(21) If(population[generation+1].size() < population_size)
	(22) population[generation+1].add(decode(pairs.second))
	(23) end If
	(24) end While
	(25) generation++
	(26) end While