Initial commit: cuGenOpt GPU optimization solver

benchmark/experiments/opt_init_solution/gpu.cu

@@ -0,0 +1,63 @@
+/**
+ * opt_init_solution: 属性双向构造初始解 验证实验
+ *
+ * 对比：heuristic init（当前代码，TSP 自动注入距离矩阵构造解）
+ *       vs E4 baseline 数据（纯随机初始解）
+ *
+ * 测试实例：eil51, lin318, pcb442
+ * 时间预算：5s, 10s, 30s
+ * 输出：CSV
+ */
+#include "bench_common.cuh"
+
+int main(int argc, char** argv) {
+    bench_init();
+    bench_csv_header();
+
+    float time_budgets[] = {5.0f, 10.0f, 30.0f};
+
+    // eil51 — 小规模回归测试
+    {
+        auto& inst = ALL_TSP_INSTANCES[0]; // eil51
+        float* dist = new float[inst.n * inst.n];
+        compute_euc2d_dist(dist, inst.coords, inst.n);
+        for (float t : time_budgets) {
+            char cfg[64];
+            snprintf(cfg, sizeof(cfg), "heur_%.0fs", t);
+            SolverConfig c = make_timed_config(t);
+            bench_run_tsp<void>(inst.name, cfg, inst.n, dist, c, inst.optimal);
+        }
+        delete[] dist;
+    }
+
+    // lin318 — 中大规模
+    {
+        auto& inst = ALL_TSP_INSTANCES[4]; // lin318
+        float* dist = new float[inst.n * inst.n];
+        compute_euc2d_dist(dist, inst.coords, inst.n);
+        for (float t : time_budgets) {
+            char cfg[64];
+            snprintf(cfg, sizeof(cfg), "heur_%.0fs", t);
+            SolverConfig c = make_timed_config(t);
+            bench_run_tsp<void>(inst.name, cfg, inst.n, dist, c, inst.optimal);
+        }
+        delete[] dist;
+    }
+
+    // pcb442 — 大规模
+    {
+        auto& inst = ALL_TSP_INSTANCES[5]; // pcb442
+        float* dist = new float[inst.n * inst.n];
+        compute_euc2d_dist(dist, inst.coords, inst.n);
+        for (float t : time_budgets) {
+            char cfg[64];
+            snprintf(cfg, sizeof(cfg), "heur_%.0fs", t);
+            SolverConfig c = make_timed_config(t);
+            bench_run_tsp<void>(inst.name, cfg, inst.n, dist, c, inst.optimal);
+        }
+        delete[] dist;
+    }
+
+    fprintf(stderr, "\n[opt_init] completed.\n");
+    return 0;
+}