mirror of
https://github.com/L-yang-yang/cugenopt.git
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136 lines
4 KiB
Python
136 lines
4 KiB
Python
"""
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标准实例解析器 — 从 TSPLIB / CVRPLIB 官方文件读取数据
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数据文件位于 data/tsplib/ 和 data/cvrplib/
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"""
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import math
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import os
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DATA_ROOT = os.path.join(os.path.dirname(os.path.dirname(__file__)), "data")
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TSPLIB_DIR = os.path.join(DATA_ROOT, "tsplib")
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CVRPLIB_DIR = os.path.join(DATA_ROOT, "cvrplib")
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def parse_tsp(filepath):
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"""解析 TSPLIB .tsp 文件（EUC_2D 格式）"""
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meta = {}
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coords = []
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reading_coords = False
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with open(filepath) as f:
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for line in f:
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line = line.strip()
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if not line:
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continue
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if line == "NODE_COORD_SECTION":
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reading_coords = True
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continue
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if line in ("EOF", "DISPLAY_DATA_SECTION"):
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break
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if reading_coords:
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parts = line.split()
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coords.append((float(parts[1]), float(parts[2])))
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else:
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if ":" in line:
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key, val = line.split(":", 1)
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meta[key.strip()] = val.strip()
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n = int(meta.get("DIMENSION", len(coords)))
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assert len(coords) == n, f"Expected {n} coords, got {len(coords)}"
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return {"name": meta.get("NAME", ""), "n": n, "coords": coords}
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def parse_vrp(filepath):
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"""解析 CVRPLIB .vrp 文件"""
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meta = {}
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coords = []
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demands = []
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section = None
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with open(filepath) as f:
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for line in f:
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line = line.strip()
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if not line:
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continue
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if line == "NODE_COORD_SECTION":
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section = "coord"
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continue
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elif line == "DEMAND_SECTION":
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section = "demand"
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continue
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elif line in ("DEPOT_SECTION", "EOF"):
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section = None
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continue
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if section == "coord":
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parts = line.split()
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coords.append((float(parts[1]), float(parts[2])))
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elif section == "demand":
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parts = line.split()
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demands.append(int(parts[1]))
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elif ":" in line:
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key, val = line.split(":", 1)
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meta[key.strip()] = val.strip()
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n = int(meta.get("DIMENSION", len(coords)))
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capacity = int(meta.get("CAPACITY", 0))
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name = meta.get("NAME", "")
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comment = meta.get("COMMENT", "")
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optimal = 0
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if "Optimal value:" in comment:
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optimal = int(comment.split("Optimal value:")[-1].strip().rstrip(")"))
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return {
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"name": name,
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"n": n,
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"coords": coords,
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"demands": demands,
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"capacity": capacity,
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"optimal": optimal,
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}
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def euc2d_dist_matrix(coords):
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"""EUC_2D 距离矩阵（四舍五入到整数，与 TSPLIB 标准一致）"""
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n = len(coords)
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dist = [[0] * n for _ in range(n)]
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for i in range(n):
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for j in range(n):
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dx = coords[i][0] - coords[j][0]
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dy = coords[i][1] - coords[j][1]
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dist[i][j] = round(math.sqrt(dx * dx + dy * dy))
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return dist
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# ============================================================
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# 预定义实例列表（文件名 → 已知最优）
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# ============================================================
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TSP_INSTANCES = [
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{"file": "eil51.tsp", "optimal": 426},
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{"file": "eil76.tsp", "optimal": 538},
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{"file": "kroA100.tsp", "optimal": 21282},
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{"file": "ch150.tsp", "optimal": 6528},
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{"file": "tsp225.tsp", "optimal": 3916},
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{"file": "lin318.tsp", "optimal": 42029},
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{"file": "pcb442.tsp", "optimal": 50778},
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]
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VRP_INSTANCES = [
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{"file": "A-n32-k5.vrp", "optimal": 784, "n_vehicles": 5},
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]
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def load_tsp(entry):
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"""加载一个 TSP 实例"""
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data = parse_tsp(os.path.join(TSPLIB_DIR, entry["file"]))
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data["optimal"] = entry["optimal"]
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return data
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def load_vrp(entry):
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"""加载一个 VRP 实例"""
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data = parse_vrp(os.path.join(CVRPLIB_DIR, entry["file"]))
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data["optimal"] = entry["optimal"]
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data["n_vehicles"] = entry["n_vehicles"]
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return data
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