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283 lines
10 KiB
Text
283 lines
10 KiB
Text
/**
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* E8: P2 约束导向 + 分层搜索策略 A/B 测试
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*
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* 对比四种配置：
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* baseline: 仅 AOS（当前默认）
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* constraint: AOS + 约束导向
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* phased: AOS + 分层搜索
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* combined: AOS + 约束导向 + 分层搜索
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*
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* 测试问题：
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* - VRP A-n32-k5（中等约束）
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* - VRPTW 8客户（高约束：容量+时间窗）
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* - Priority-VRP A-n32-k5（高约束：容量+优先级偏序）
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* - TSP eil51（无约束 baseline，验证无回退）
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*
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* 时间预算：5s, 15s
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*/
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#include "bench_common.cuh"
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struct PriorityVRPProblem : ProblemBase<PriorityVRPProblem, 8, 64> {
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const float* d_dist;
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const float* d_demand;
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const int* d_priority;
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const float* h_dist;
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int n, stride;
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float capacity;
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int num_vehicles, max_vehicles;
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GpuCache cache;
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__device__ float compute_route_dist(const int* route, int size) const {
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if (size == 0) return 0.0f;
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float dist = 0.0f;
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int prev = 0;
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for (int j = 0; j < size; j++) {
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int node = route[j] + 1;
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dist += d_dist[prev * stride + node];
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prev = node;
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}
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dist += d_dist[prev * stride + 0];
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return dist;
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}
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__device__ float calc_total_distance(const Sol& sol) const {
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float total = 0.0f;
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for (int r = 0; r < num_vehicles; r++)
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total += compute_route_dist(sol.data[r], sol.dim2_sizes[r]);
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return total;
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}
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static constexpr ObjDef OBJ_DEFS[] = {{ObjDir::Minimize, 1.0f, 0.0f}};
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__device__ float compute_obj(int, const Sol& sol) const { return calc_total_distance(sol); }
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__device__ float compute_penalty(const Sol& sol) const {
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float pen = 0.0f;
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int active = 0;
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for (int r = 0; r < num_vehicles; r++) {
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int size = sol.dim2_sizes[r];
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if (size == 0) continue;
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active++;
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float load = 0.0f;
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for (int j = 0; j < size; j++) load += d_demand[sol.data[r][j]];
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if (load > capacity) pen += (load - capacity) * 100.0f;
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int min_prio_seen = 3;
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for (int j = 0; j < size; j++) {
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int p = d_priority[sol.data[r][j]];
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if (p > min_prio_seen) pen += (float)(p - min_prio_seen) * 50.0f;
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if (p < min_prio_seen) min_prio_seen = p;
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}
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}
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if (active > max_vehicles) pen += (float)(active - max_vehicles) * 1000.0f;
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return pen;
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}
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ProblemConfig config() const {
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ProblemConfig cfg;
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cfg.encoding = EncodingType::Permutation;
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cfg.dim1 = num_vehicles; cfg.dim2_default = 0;
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fill_obj_config(cfg);
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cfg.cross_row_prob = 0.3f;
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cfg.row_mode = RowMode::Partition;
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cfg.total_elements = n;
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return cfg;
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}
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static constexpr size_t SMEM_LIMIT = 48 * 1024;
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size_t shared_mem_bytes() const {
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size_t total = (size_t)stride * stride * sizeof(float)
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+ (size_t)n * sizeof(float) + (size_t)n * sizeof(int);
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return total <= SMEM_LIMIT ? total : 0;
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}
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size_t working_set_bytes() const {
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return (size_t)stride * stride * sizeof(float)
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+ (size_t)n * sizeof(float) + (size_t)n * sizeof(int);
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}
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__device__ void load_shared(char* smem, int tid, int bsz) {
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float* sd = reinterpret_cast<float*>(smem);
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int dist_size = stride * stride;
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for (int i = tid; i < dist_size; i += bsz) sd[i] = d_dist[i];
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d_dist = sd;
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float* sdem = sd + dist_size;
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for (int i = tid; i < n; i += bsz) sdem[i] = d_demand[i];
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d_demand = sdem;
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int* spri = reinterpret_cast<int*>(sdem + n);
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for (int i = tid; i < n; i += bsz) spri[i] = d_priority[i];
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d_priority = spri;
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}
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void init_relation_matrix(float* G, float* O, int N) const {
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if (!h_dist || N != n) return;
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float max_d = 0.0f;
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for (int i = 0; i < N; i++)
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for (int j = 0; j < N; j++) {
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float d = h_dist[(i+1)*stride+(j+1)];
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if (d > max_d) max_d = d;
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}
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if (max_d <= 0.0f) return;
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for (int i = 0; i < N; i++)
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for (int j = 0; j < N; j++) {
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if (i == j) continue;
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float d = h_dist[(i+1)*stride+(j+1)];
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float prox = 1.0f - d / max_d;
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G[i*N+j] = prox * 0.3f;
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O[i*N+j] = prox * 0.1f;
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}
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}
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static PriorityVRPProblem create(const float* h_dist_ptr, const float* h_demand,
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const int* h_priority, int n, float cap,
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int nv, int mv) {
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PriorityVRPProblem prob;
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prob.n = n; prob.stride = n+1; prob.capacity = cap;
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prob.num_vehicles = nv; prob.max_vehicles = mv;
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prob.cache = GpuCache::disabled(); prob.h_dist = h_dist_ptr;
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int nn = n+1;
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float* dd; CUDA_CHECK(cudaMalloc(&dd, sizeof(float)*nn*nn));
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CUDA_CHECK(cudaMemcpy(dd, h_dist_ptr, sizeof(float)*nn*nn, cudaMemcpyHostToDevice));
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prob.d_dist = dd;
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float* ddem; CUDA_CHECK(cudaMalloc(&ddem, sizeof(float)*n));
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CUDA_CHECK(cudaMemcpy(ddem, h_demand, sizeof(float)*n, cudaMemcpyHostToDevice));
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prob.d_demand = ddem;
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int* dpri; CUDA_CHECK(cudaMalloc(&dpri, sizeof(int)*n));
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CUDA_CHECK(cudaMemcpy(dpri, h_priority, sizeof(int)*n, cudaMemcpyHostToDevice));
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prob.d_priority = dpri;
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return prob;
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}
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void destroy() {
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if (d_dist) { cudaFree(const_cast<float*>(d_dist)); d_dist = nullptr; }
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if (d_demand) { cudaFree(const_cast<float*>(d_demand)); d_demand = nullptr; }
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if (d_priority) { cudaFree(const_cast<int*>(d_priority)); d_priority = nullptr; }
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h_dist = nullptr; cache.destroy();
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}
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};
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static const int an32k5_priority[AN32K5_N] = {
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2,2,2,2,2,2,2,2,2,2, 1,1,1,1,1,1,1,1,1,1,1, 0,0,0,0,0,0,0,0,0,0
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};
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struct ConfigVariant {
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const char* name;
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bool constraint_directed;
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bool phased_search;
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};
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static const ConfigVariant VARIANTS[] = {
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{"baseline", false, false},
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{"constraint", true, false},
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{"phased", false, true},
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{"combined", true, true},
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};
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static const int NUM_VARIANTS = 4;
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static SolverConfig make_p2_config(float seconds, const ConfigVariant& v) {
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SolverConfig c = make_timed_config(seconds);
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c.use_constraint_directed = v.constraint_directed;
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c.use_phased_search = v.phased_search;
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return c;
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}
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static void run_vrp() {
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fprintf(stderr, "\n=== VRP A-n32-k5 ===\n");
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float dist[AN32K5_NODES * AN32K5_NODES];
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compute_euc2d_dist(dist, an32k5_coords, AN32K5_NODES);
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float budgets[] = {5.0f, 15.0f};
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for (float t : budgets) {
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for (int v = 0; v < NUM_VARIANTS; v++) {
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char cfg_name[64];
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snprintf(cfg_name, sizeof(cfg_name), "%s_%.0fs", VARIANTS[v].name, t);
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SolverConfig c = make_p2_config(t, VARIANTS[v]);
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bench_run_recreate("VRP-A32k5", cfg_name,
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[&]() { return VRPProblem::create(dist, an32k5_demands, AN32K5_N, 100.0f, 5, 5); },
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c, 784.0f);
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}
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}
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}
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static void run_vrptw() {
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fprintf(stderr, "\n=== VRPTW 8-customer ===\n");
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const int N = 8;
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const int NODES = N + 1;
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float coords[NODES][2] = {
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{40,40}, {22,22},{36,26},{21,45},{45,35},{55,20},{33,34},{50,50},{55,45}
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};
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float demand[N] = {10,20,10,10,20,10,20,10};
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float earliest[NODES] = {0, 0, 5, 0, 10, 0, 0, 15, 0};
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float latest[NODES] = {999,50,40,60,80,45,70,90,55};
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float service[NODES] = {0, 10,10,10,10,10,10,10,10};
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float capacity = 40.0f;
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int num_vehicles = 3, max_vehicles = 3;
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float dist[NODES * NODES];
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for (int i = 0; i < NODES; i++)
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for (int j = 0; j < NODES; j++) {
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float dx = coords[i][0] - coords[j][0];
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float dy = coords[i][1] - coords[j][1];
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dist[i * NODES + j] = sqrtf(dx*dx + dy*dy);
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}
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float budgets[] = {5.0f, 15.0f};
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for (float t : budgets) {
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for (int v = 0; v < NUM_VARIANTS; v++) {
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char cfg_name[64];
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snprintf(cfg_name, sizeof(cfg_name), "%s_%.0fs", VARIANTS[v].name, t);
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SolverConfig c = make_p2_config(t, VARIANTS[v]);
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bench_run_recreate("VRPTW-8", cfg_name,
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[&]() {
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return VRPTWProblem::create(
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dist, demand, earliest, latest, service,
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N, capacity, num_vehicles, max_vehicles);
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},
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c, 0.0f);
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}
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}
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}
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static void run_priority_vrp() {
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fprintf(stderr, "\n=== Priority-VRP A-n32-k5 ===\n");
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float dist[AN32K5_NODES * AN32K5_NODES];
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compute_euc2d_dist(dist, an32k5_coords, AN32K5_NODES);
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float budgets[] = {5.0f, 15.0f};
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for (float t : budgets) {
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for (int v = 0; v < NUM_VARIANTS; v++) {
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char cfg_name[64];
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snprintf(cfg_name, sizeof(cfg_name), "%s_%.0fs", VARIANTS[v].name, t);
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SolverConfig c = make_p2_config(t, VARIANTS[v]);
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bench_run_recreate("PrioVRP-A32k5", cfg_name,
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[&]() {
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return PriorityVRPProblem::create(
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dist, an32k5_demands, an32k5_priority,
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AN32K5_N, 100.0f, 5, 5);
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},
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c, 784.0f);
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}
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}
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}
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static void run_tsp_sanity() {
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fprintf(stderr, "\n=== TSP eil51 (sanity check, no constraints) ===\n");
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float dist[EIL51_N * EIL51_N];
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compute_euc2d_dist(dist, eil51_coords, EIL51_N);
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float budgets[] = {5.0f};
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for (float t : budgets) {
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for (int v = 0; v < NUM_VARIANTS; v++) {
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char cfg_name[64];
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snprintf(cfg_name, sizeof(cfg_name), "%s_%.0fs", VARIANTS[v].name, t);
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SolverConfig c = make_p2_config(t, VARIANTS[v]);
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bench_run_tsp<void>("eil51", cfg_name, EIL51_N, dist, c, 426.0f, 3);
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}
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}
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}
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int main() {
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bench_init();
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bench_csv_header();
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run_vrp();
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run_vrptw();
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run_priority_vrp();
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run_tsp_sanity();
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fprintf(stderr, "\n[e8] P2 search strategy A/B test completed.\n");
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return 0;
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}
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