Fast heuristic for constrained homogenous T-shape cutting patterns

A recursive branch-and-bound algorithm for constrained homogenous T-shape cutting patterns

A population heuristic for constrained two-dimensional non-guillotine cutting

A Hybrid Heuristic for the Constrained Two-dimensional Non-guillotine Orthogonal Cutting Problem

This paper addresses a constrained two-dimensional (2D) non-guillotine cutting problem, where a fixed set of small rectangles has to be cut from a larger stock rectangle so as to maximize the value of the rectangles cut. The algorithm we propose hybridizes a novel placement procedure with a genetic algorithm based on random keys. We propose also a new fitness function to drive the optimization....

A Novel Fast Heuristic to Handle Large-Scale Shape Clustering

Clustering algorithms like types of k-means are fast, but they are inefficient for shape clustering. There are some algorithms, which are effective, but their time complexities are too high. This paper proposes a novel heuristic to solve large-scale shape clustering. The proposed method is effective and it solves large-scale clustering problems in fraction of a second.

Column generation and sequential heuristic procedure for solving an irregular shape cutting stock problem

Research addressing two-dimensional irregular shape packing has largely focused on the strip packing variant of the problem. However, it can be argued that this is a simplification. Materials from which pieces are required to be cut will ultimately have a fixed length either due to the physical dimensions of the material or through constraints on the cutting machinery. Hence, in order to cut al...