C++ population::champion方法代码示例

void ms::evolve(population &pop) const
{
	// Let's store some useful variables.
	const population::size_type NP = pop.size();

	// Get out if there is nothing to do.
	if (m_starts == 0 || NP == 0) {
		return;
	}

	// Local population used in the algorithm iterations.
	population working_pop(pop);

	//ms main loop
	for (int i=0; i< m_starts; ++i)
	{
		working_pop.reinit();
		m_algorithm->evolve(working_pop);
		if (working_pop.problem().compare_fc(working_pop.get_individual(working_pop.get_best_idx()).cur_f,working_pop.get_individual(working_pop.get_best_idx()).cur_c,
			pop.get_individual(pop.get_worst_idx()).cur_f,pop.get_individual(pop.get_worst_idx()).cur_c
		) )
		{
			//update best population replacing its worst individual with the good one just produced.
			pop.set_x(pop.get_worst_idx(),working_pop.get_individual(working_pop.get_best_idx()).cur_x);
			pop.set_v(pop.get_worst_idx(),working_pop.get_individual(working_pop.get_best_idx()).cur_v);
		}
		if (m_screen_output)
		{
			std::cout << i << ". " << "\tCurrent iteration best: " << working_pop.get_individual(working_pop.get_best_idx()).cur_f << "\tOverall champion: " << pop.champion().f << std::endl;
		}
	}
}

//.........这里部分代码省略.........
	}
	if(prob.get_f_dimension() != 1) {
		pagmo_throw(value_error,"The problem is multiobjective and CORE is not suitable to solve it");
	}

	// Get out if there is nothing to do.
	if(pop_size == 0) {
		return;
	}

	// generates the unconstrained problem
	problem::con2uncon prob_unconstrained(prob);

	// associates the population to this problem
	population pop_uncon(prob_unconstrained);

	// fill this unconstrained population
	pop_uncon.clear();
	for(population::size_type i=0; i<pop_size; i++) {
		pop_uncon.push_back(pop.get_individual(i).cur_x);
	}

	// vector containing the infeasibles positions
	std::vector<population::size_type> pop_infeasibles;

	// Main CORE loop
	for(int k=0; k<m_gen; k++) {

		if(k%m_repair_frequency == 0) {
			pop_infeasibles.clear();

			// get the infeasible individuals
			for(population::size_type i=0; i<pop_size; i++) {
				if(!prob.feasibility_c(pop.get_individual(i).cur_c)) {
					pop_infeasibles.push_back(i);
				}
			}

			// random shuffle of infeasibles?
			population::size_type number_of_repair = (population::size_type)(m_repair_ratio * pop_infeasibles.size());

			// repair the infeasible individuals
			for(population::size_type i=0; i<number_of_repair; i++) {
				const population::size_type &current_individual_idx = pop_infeasibles.at(i);

                pop.repair(current_individual_idx, m_repair_algo);
			}

			// the population is repaired, it can be now used in the new unconstrained population
			// only the repaired individuals are put back in the population
			for(population::size_type i=0; i<number_of_repair; i++) {
				population::size_type current_individual_idx = pop_infeasibles.at(i);
				pop_uncon.set_x(current_individual_idx, pop.get_individual(current_individual_idx).cur_x);
			}
		}

		m_original_algo->evolve(pop_uncon);

		// push back the population in the main problem
		pop.clear();
		for(population::size_type i=0; i<pop_size; i++) {
			pop.push_back(pop_uncon.get_individual(i).cur_x);
		}

		// Check the exit conditions (every 40 generations, just as DE)
		if(k % 40 == 0) {
			decision_vector tmp(prob_dimension);

			double dx = 0;
			for(decision_vector::size_type i=0; i<prob_dimension; i++) {
				tmp[i] = pop.get_individual(pop.get_worst_idx()).best_x[i] - pop.get_individual(pop.get_best_idx()).best_x[i];
				dx += std::fabs(tmp[i]);
			}

			if(dx < m_xtol ) {
				if (m_screen_output) {
					std::cout << "Exit condition -- xtol < " << m_xtol << std::endl;
				}
				break;
			}

			double mah = std::fabs(pop.get_individual(pop.get_worst_idx()).best_f[0] - pop.get_individual(pop.get_best_idx()).best_f[0]);

			if(mah < m_ftol) {
				if(m_screen_output) {
					std::cout << "Exit condition -- ftol < " << m_ftol << std::endl;
				}
				break;
			}

			// outputs current values
			if(m_screen_output) {
				std::cout << "Generation " << k << " ***" << std::endl;
				std::cout << "    Best global fitness: " << pop.champion().f << std::endl;
				std::cout << "    xtol: " << dx << ", ftol: " << mah << std::endl;
				std::cout << "    xtol: " << dx << ", ftol: " << mah << std::endl;
			}
		}
	}
}