Metaheuristics for the Minimum Time Cut Path Problem with Different Cutting and Sliding Speeds

The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurrent in several manufacturing settings. This problem belongs to the domain of cutting and packing (C&P) problems. This study approached a category of C&P problems called the minimum time cut path (MTCP) problem, which aims to identify a sequence of cutting and sliding movements for the head device to minimize manufacturing time. Both cutting and slide speeds (just moving the head) vary according to equipment, despite their relevance in real-world scenarios. This study applied the MTCP problem on the practical scope and presents two metaheuristics for tackling more significant instances that resemble real-world requirements. The experiments presented in this study utilized parameter values from typical laser cutting machines to assess the feasibility of the proposed methods compared to existing commercial software. The results show that metaheuristic-based solutions are competitive when addressing practical problems, achieving increased performance regarding the processing time for 94% of the instances.

2DPackLib: a two-dimensional cutting and packing library

Two-dimensional cutting and packing problems model a large number of relevant industrial applications.The literature on practical algorithms for such problems is very large. We introduce the , a library on two-dimensional orthogonal cutting and packing problems. The library makes available, in a unified format, 25 benchmarks from the literature for a total of over 3000 instances, provides direct links to surveys and typologies, and includes a list of relevant links.

The integrated cutting and packing heterogeneous precast beams multiperiod production planning problem

We introduce a novel variant of cutting production planning problems named Integrated Cutting and Packing Heterogeneous Precast Beams Multiperiod Production Planning (ICP-HPBMPP). We propose an integer linear programming model for the ICP-HPBMPP, as well as a lower bound for its optimal objective function value, which is empirically shown to be closer to the optimal solution value than the bound obtained from the linear relaxation of the model. We also propose a genetic algorithm approach for the ICP-HPBMPP as an alternative solution method. We discuss computational experiments and propose a parameterization for the genetic algorithm using D-optimal experimental design. We observe good performance of the exact approach when solving small-sized instances, although there are difficulties in finding optimal solutions for medium and large-sized problems, or even in finding feasible solutions for large instances. On the other hand, the genetic algorithm is shown to typically find good-quality solutions for large-sized instances within short computing times.

Algorithms for Working with Orthogonal Polyhedrons in Solving Cutting and Packing Problems

In this paper problems of cutting and packing objects of complex geometric shapes are considered. To solve these NP-hard problems, it is proposed to use an approach based on geometric transformation of polygonal objects to composite objects (orthogonal polyhedrons) made up of rectangles or parallelepipeds of a given dimension. To describe the free space inside a voxelized container, a model of potential containers is used as the basic model that provides the ability of packing orthogonal polyhedrons. A number of specialized algorithms are developed to work with orthogonal polyhedrons including: algorithms for placing and removing composite objects, an algorithm for forming a packing with a given distance between objects to be placed. Two algorithms for the placement of orthogonal polyhedrons are developed and their efficiency is investigated. An algorithm for obtaining a container of complex shape presented as an orthogonal polyhedron based on a polygonal model is given. The article contains examples of placement schemes obtained by the developed algorithms for solving problems of packing two-dimensional and three-dimensional non-rectangular composite objects.

Descending Packing Algorithm for Irregular Graphics Based on Geometric Feature Points

The packing for two-dimensional irregular graphics is one of the NP-complete problems and widely used in industrial applications. In this paper, a descending nesting algorithm for a two-dimensional irregular graph based on geometric feature points is proposed. Before the packing, the parts to be packed are sorted, matched, and spliced, and the matching of the rectangular pieces and the rectangular-like pieces is carried out according to the plate size. On this basis, the geometric feature points of the parts are used to construct the packing baseline, and the packing is accurately carried out according to the principles of the bottom left, the principle of the lowest center of gravity, and combination with virtual moving, rotating collision calculation. The computation of the moving collision distance between the graphics is replaced by the projecting computation of the geometric feature points of the graphic parts, so the computation amount can be reduced. Also, this method is used to test a number of benchmarks examples which are provided by ESICUP (EURO Special Interest Group on Cutting and Packing), which show that the proposed algorithm not only can improve packing but also has better stability and reliability.