Developing a simulated annealing algorithm for the cutting stock problem
Computers and Industrial Engineering
Recent advances on two-dimensional bin packing problems
Discrete Applied Mathematics
An Exact Approach to the Strip-Packing Problem
INFORMS Journal on Computing
An Exact Algorithm for Constrained Two-Dimensional Two-Staged Cutting Problems
Operations Research
A new heuristic recursive algorithm for the strip rectangular packing problem
Computers and Operations Research
A new heuristic algorithm for rectangle packing
Computers and Operations Research
A New Placement Heuristic for the Orthogonal Stock-Cutting Problem
Operations Research
Reactive GRASP for the strip-packing problem
Computers and Operations Research
A recursive branch-and-bound algorithm for the rectangular guillotine strip packing problem
Computers and Operations Research
The Bottomn-Left Bin-Packing Heuristic: An Efficient Implementation
IEEE Transactions on Computers
A least wasted first heuristic algorithm for the rectangular packing problem
Computers and Operations Research
An Exact Algorithm for Higher-Dimensional Orthogonal Packing
Operations Research
A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock-Cutting Problem
INFORMS Journal on Computing
A simple randomized algorithm for two-dimensional strip packing
Computers and Operations Research
Hybrid approach for 2d strip packing problem using genetic algorithm
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
| Hi-index | 12.05 |
In this paper, an orthogonal strip packing problem with rotation of items and without the guillotine packing constraint is considered. A fast heuristic algorithm for the large-scale problems is presented. This heuristic algorithm is mainly based on heuristic strategies inspired by the wall-building rule of bricklayers in daily life. The heuristics is simple and the setting of parameter is not required. Each layer is initialized with either a single item or a bunch of equal-width items. The remaining part of the layer is filled by a bottom-left strategy preferring items which eliminate corners of the current layout. Items can also be placed across several layers. Then, the evaluation rule, which is based on the fitness value for different rectangles to a given position, is able to select an appropriate rectangle to pack. The computational results on a broad range of benchmark problems show that the fast layer-based heuristic algorithm can compete with other latest heuristics and meta-heuristics from the literature in terms of both solution quality and computational time. The fast layer-based heuristic algorithm can compete with the latest published algorithms. In particular, it performs better for large-scale problem instances.