cuGenOpt/python/cugenopt/include/problems/vrp.cuh
2026-03-20 00:33:45 +08:00

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/**
* vrp.cuh - 容量约束车辆路径问题 (CVRP)
*
* 继承 ProblemBase使用 ObjDef 目标注册机制
* 多行编码D1=K 条路线,分区初始化 + 跨行算子)
*/
#pragma once
#include "types.cuh"
#include "cuda_utils.cuh"
#include "operators.cuh"
#include "gpu_cache.cuh"
struct VRPProblem : ProblemBase<VRPProblem, 8, 64> {
// GPU 数据
const float* d_dist;
const float* d_demand;
const float* h_dist; // host 端距离矩阵(含 depot用于 init_relation_matrix
int n;
int stride;
float capacity;
int num_vehicles;
int max_vehicles;
GpuCache cache;
// ---- 目标计算 ----
__device__ float compute_route_dist(const int* route, int size) const {
if (size == 0) return 0.0f;
float dist = 0.0f;
int prev = 0;
for (int j = 0; j < size; j++) {
int node = route[j] + 1;
dist += d_dist[prev * stride + node];
prev = node;
}
dist += d_dist[prev * stride + 0];
return dist;
}
__device__ float eval_route(const int* route, int size) const {
if (size == 0) return 0.0f;
if (!cache.keys) return compute_route_dist(route, size);
uint64_t key = route_hash(route, size);
float dist;
if (cache_lookup(cache, key, dist)) {
atomicAdd(cache.d_hits, 1);
return dist;
}
dist = compute_route_dist(route, size);
cache_insert(cache, key, dist);
atomicAdd(cache.d_misses, 1);
return dist;
}
__device__ float calc_total_distance(const Sol& sol) const {
float total = 0.0f;
for (int r = 0; r < num_vehicles; r++)
total += eval_route(sol.data[r], sol.dim2_sizes[r]);
return total;
}
// ---- 目标定义OBJ_DEFS 与 compute_obj 必须一一对应)----
static constexpr ObjDef OBJ_DEFS[] = {
{ObjDir::Minimize, 1.0f, 0.0f}, // case 0: calc_total_distance
};
__device__ float compute_obj(int idx, const Sol& sol) const {
switch (idx) {
case 0: return calc_total_distance(sol); // OBJ_DEFS[0]
default: return 0.0f;
}
}
__device__ float compute_penalty(const Sol& sol) const {
float penalty = 0.0f;
int active = 0;
for (int r = 0; r < num_vehicles; r++) {
int size = sol.dim2_sizes[r];
if (size == 0) continue;
active++;
float load = 0.0f;
for (int j = 0; j < size; j++)
load += d_demand[sol.data[r][j]];
if (load > capacity)
penalty += (load - capacity) * 100.0f;
}
if (active > max_vehicles)
penalty += (float)(active - max_vehicles) * 1000.0f;
return penalty;
}
ProblemConfig config() const {
ProblemConfig cfg;
cfg.encoding = EncodingType::Permutation;
cfg.dim1 = num_vehicles;
cfg.dim2_default = 0;
fill_obj_config(cfg);
cfg.cross_row_prob = 0.3f;
cfg.row_mode = RowMode::Partition;
cfg.total_elements = n;
return cfg;
}
// ---- shared memory 接口 ----
static constexpr size_t SMEM_LIMIT = 48 * 1024;
size_t shared_mem_bytes() const {
size_t dist_bytes = (size_t)stride * stride * sizeof(float);
size_t demand_bytes = (size_t)n * sizeof(float);
size_t total = dist_bytes + demand_bytes;
return total <= SMEM_LIMIT ? total : 0;
}
size_t working_set_bytes() const {
return (size_t)stride * stride * sizeof(float) + (size_t)n * sizeof(float);
}
__device__ void load_shared(char* smem, int tid, int bsz) {
float* sd = reinterpret_cast<float*>(smem);
int dist_size = stride * stride;
for (int i = tid; i < dist_size; i += bsz) sd[i] = d_dist[i];
d_dist = sd;
float* sdem = sd + dist_size;
for (int i = tid; i < n; i += bsz) sdem[i] = d_demand[i];
d_demand = sdem;
}
void enable_cache(int cap = 65536) { cache = GpuCache::allocate(cap); }
void print_cache_stats() const { cache.print_stats(); }
// 距离先验:客户间距离近 → G/O 分数高
// 注意h_dist 含 depotstride×stride元素编号 0..n-1 对应 node 1..n
void init_relation_matrix(float* G, float* O, int N) const {
if (!h_dist || N != n) return;
float max_d = 0.0f;
for (int i = 0; i < N; i++)
for (int j = 0; j < N; j++) {
float d = h_dist[(i + 1) * stride + (j + 1)]; // 跳过 depot
if (d > max_d) max_d = d;
}
if (max_d <= 0.0f) return;
for (int i = 0; i < N; i++)
for (int j = 0; j < N; j++) {
if (i == j) continue;
float d = h_dist[(i + 1) * stride + (j + 1)];
float proximity = 1.0f - d / max_d;
G[i * N + j] = proximity * 0.3f;
O[i * N + j] = proximity * 0.1f;
}
}
static VRPProblem create(const float* h_dist_ptr, const float* h_demand,
int n, float capacity,
int num_vehicles, int max_vehicles) {
VRPProblem prob;
prob.n = n;
prob.stride = n + 1;
prob.capacity = capacity;
prob.num_vehicles = num_vehicles;
prob.max_vehicles = max_vehicles;
prob.cache = GpuCache::disabled();
prob.h_dist = h_dist_ptr;
int n_nodes = n + 1;
float* dd;
CUDA_CHECK(cudaMalloc(&dd, sizeof(float) * n_nodes * n_nodes));
CUDA_CHECK(cudaMemcpy(dd, h_dist_ptr, sizeof(float) * n_nodes * n_nodes, cudaMemcpyHostToDevice));
prob.d_dist = dd;
float* ddem;
CUDA_CHECK(cudaMalloc(&ddem, sizeof(float) * n));
CUDA_CHECK(cudaMemcpy(ddem, h_demand, sizeof(float) * n, cudaMemcpyHostToDevice));
prob.d_demand = ddem;
return prob;
}
void destroy() {
if (d_dist) { cudaFree(const_cast<float*>(d_dist)); d_dist = nullptr; }
if (d_demand) { cudaFree(const_cast<float*>(d_demand)); d_demand = nullptr; }
h_dist = nullptr;
cache.destroy();
}
};