This repository contains algorithms for 2D irregular packing and a simple tutorial to the algorithms. If you discover any issues with the code, you are welcome to fork the repository and initiate a pull request after you have tested the code. We will review the changes and, upon confirmation, integrate them into the main branch and acknowledge you as one of our contributors.
Literature Review：排样问题文献综述/教程（中文） Yang shan
Author: Shan Yang, Zilu Wang (Department of Science and Managment, Tongji University)
Email: tjyangshan@gmail.com, prinway1226@gmail.com
Yang is working in Dr. Xiaolei Wang's laboratory on optimization problems in urban transportation. Wang is working in Dr. Zhaolin Hu's laboratory on random optimization and simulation. Our work in 2D irregular packing is encouraged by Dr. Zhe Liang in our department. Welcome to chat with us on these topics.
EURO Dataset：https://www.euro-online.org/websites/esicup/data-sets/#1535972088237-bbcb74e3-b507
Data sets have been processed to csv in folder data.
import pandas as pd
import json
df = pd.read_csv("data/blaz1.csv")
all_polys = []
for i in range(df.shape[0]):
all_polys.append(df['polygon'][i])
print(all_polys)Bottom-Left-Fill.py: A 2-exchange heuristic for nesting problems 2002
genetic_algorithm.py: A 2-exchange heuristic for nesting problems 2002
nfp_test.py: Complete and robust no-fit polygon generation for the irregular stock cutting problem.
Cuckoo_search.py: A new approach for sheet nesting problem using guided cuckoo search and pairwise clustering
Fast_neighbor_search.py: 2004 Fast neighborhood search for two- and three-dimensional nesting problems
simulating_annealing.py: SA+Bottom left fill
lp_algorithm.py: Solving Irregular Strip Packing problems by hybridising simulated annealing and linear programming 2006
lp_search.py: A new algorithm proposed by us. https://github.com/seanys/Use-Modified-Penetration-Depth-and-Guided-Search-to-Solve-Nesting-Problem.
C++ Nesting Problem: C++ Version
Most of them can work. Very small overlap is allowed in lp_search to avoid endless search.
Editing....
- No-fit Polygon：基本实现，Start Point的部分暂未实现，参考论文 Burke E K , Hellier R S R , Kendall G , et al. Complete and Robust No-Fit Polygon Generation for the Irregular Stock Cutting Problem[J]. European Journal of Operational Research, 2007, 179(1):27-49.
形状A固定位置，在B上选择一个参考点比如左下角点P，形状B紧贴着绕A一周，P的轨迹会形成一个形状即NFP，P在NFP上或外部，则该排列可行；如果P点在NFP内，则方案不可行（图片来源）
- Bottom Left Fill：已经实现，参考论文
a. 选择一个形状加入，通过计算inner fit polygon，也就是形状绕着Bin/Region内部一周，参考点P会形成的一个长方形，P点在该长方形内部则解是feasible solution
b. 选择能够摆到的最左侧位置，放进去即可 （图片来源）
- TOPOS：已经实现，参考论文：
- GA/SA：两个优化算法优化顺序已经实现
- Fast Neighborhood Search：基本实现，有一些Bug还需要修改
- Cuckoo Search：基本算法已经实现，需要进一步完善
-
ILSQN：不准备写了，没太大意义 -
Guided Local Search：同上
- Compaction：压缩边界，已经实现
- Separation：去除重叠，已经实现
- SHAH：基于模拟退火算法和上述两个算法的Hybrid Algorithm，暂时未做