我尝试在C++中并行化一个for循环，但是每次我尝试将这个循环用于更大的数据集时，我都会得到这个错误：返回的过程-1073741819（0xC 0000005）
对于小的数据集，循环可以工作，对于大的数据集，初始化可以工作，但是在这之后，我得到了内存错误。我使用的是Codeblocks和GNU GCC编译器。在这个循环中，我想运行优化进化启发式的几次迭代。我使用的是openmp，并试图将在几个线程中使用的变量置于私有状态。

#include <omp.h>

void search_framework(Data &data, Solution &best_s)
{
    vector<Solution> pop(data.p_size);
    vector<Solution> child(data.p_size);
    for (int i = 0; i < data.p_size; i++)
    {
        pop[i].reserve(data);
        child[i].reserve(data);
    }

    // parent index in pop
    vector<tuple<int, int>> p_indice(data.p_size);
    bool time_exhausted = false;
    int run = 1;
    #pragma omp parallel for firstprivate(pop, pop_fit, pop_argrank, child, child_fit, child_argrank, p_indice)
    for (int run = 1; run <= data.runs; run++)
    {
        run++;
        int no_improve = 0;
        int gen = 0;
        initialization(pop, pop_fit, pop_argrank, data);
        local_search(pop, pop_fit, pop_argrank, data);

        while (!termination(no_improve, data))
        {
            gen++;
            // printf("---------------------------------Gen %d---------------------------\n", gen);
            no_improve++;
            // select parents
            select_parents(pop, pop_fit, p_indice, data);
            // do local search for children
            local_search(child, child_fit, child_argrank, data);
            // replacement
            replacement(pop, p_indice, child, pop_fit, pop_argrank, child_fit, child_argrank, data);
            // update best
            argsort(pop_fit, pop_argrank, data.p_size);
            update_best_solution(pop[pop_argrank[0]], best_s, used, run, gen, data);
            if (data.tmax != NO_LIMIT && used > clock_t(data.tmax))
            {
                time_exhausted = true;
                break;
            }
        }
        if (time_exhausted) run = data.runs;
    }
}

编辑：这是pop等初始化的部分：

void initialization(vector<Solution> &pop, vector<double> &pop_fit, vector<int> &pop_argrank, Data &data)
{
    int len = int(pop.size());
    for (int i = 0; i < len; i++)
    {
        pop[i].clear(data);
    }
   for (int i = 0; i < len; i++)
   {
            data.lambda_gamma = data.latin[i];
            new_route_insertion(pop[i], data);
   }
    for (int i = 0; i < len; i++)
    {
        pop_fit[i] = pop[i].cost;
    }
    argsort(pop_fit, pop_argrank, len);
}