Algorithms for cutting and packing problems

Orientador: Flávio Keidi MiyazawaTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Problemas de Corte e Empacotamento são, em sua maioria, NP-difíceis e não existem algoritmos exatos de tempo polinomial para tais se for considerado P ¿ NP. Aplicações práticas envolvendo estes problemas incluem a alocação de recursos para computadores; o corte de chapas de ferro, de madeira, de vidro, de alumínio, peças em couro, etc.; a estocagem de objetos; e, o carregamento de objetos dentro de contêineres ou caminhões-baú. Nesta tese investigamos problemas de Corte e Empacotamento NP-difíceis, nas suas versões bi- e tridimensionais, considerando diversas restrições práticas impostas a tais, a saber: que permitem a rotação ortogonal dos itens; cujos cortes sejam feitos por uma guilhotina; cujos cortes sejam feitos por uma guilhotina respeitando um número máximo de estágios de corte; cujos cortes sejam não-guilhotinados; cujos itens tenham demanda (não) unitária; cujos recipientes tenham tamanhos diferentes; cujos itens sejam representados por polígonos convexos e não-convexos (formas irregulares); cujo empacotamento respeite critérios de estabilidade para corpos rígidos; cujo empacotamento satisfaça uma dada ordem de descarregamento; e, cujos empacotamentos intermediários e final tenham seu centro de gravidade dentro de uma região considerada "segura". Para estes problemas foram propostos algoritmos baseados em programação dinâmica; modelos de programação inteira; técnicas do tipo branch-and-cut; heurísticas, incluindo as baseadas na técnica de geração de colunas; e, meta-heurísticas como o GRASP. Resultados teóricos também foram obtidos. Provamos uma questão em aberto levantada na literatura sobre cortes não-guilhotinados restritos a um conjunto de pontos. Uma extensiva série de testes computacionais considerando instâncias reais e várias outras geradas de forma aleatória foram realizados com os algoritmos desenvolvidos. Os resultados computacionais, sendo alguns deles comparados com a literatura, comprovam a validade dos algoritmos propostos e a sua aplicabilidade prática para resolver os problemas investigadosAbstract: Several versions of Cutting and Packing problems are considered NP-hard and, if we consider that P ¿ NP, we do not have any exact polynomial algorithm for solve them. Practical applications arises for such problems and include: resources allocation for computers; cut of steel, wood, glass, aluminum, etc.; packing of objects; and, loading objects into containers and trucks. In this thesis we investigate Cutting and Packing problems that are NP-hard considering theirs two- and three-dimensional versions, and subject to several practical constraints, that are: that allows the items to be orthogonally rotated; whose cuts are guillotine type; whose cuts are guillotine type and performed in at most k stages; whose cuts are non-guillotine type; whose items have varying and unit demand; whose bins are of variable sizes; whose items are represented by convex and non-convex polygons (irregular shapes); whose packing must satisfy the conditions for static equilibrium of rigid bodies; whose packing must satisfy an order to unloading; and, whose intermediaries and resultant packing have theirs center of gravity inside a safety region; Such cutting and packing problems were solved by dynamic programming algorithms; integer linear programming models; branch-and-cut algorithms; several heuristics, including those ones based on column generation approaches, and metaheuristics like GRASP. Theoretical results were also provided, so a recent open question arised by literature about non-guillotine patterns restricted to a set of points was demonstrated. We performed an extensive series of computational experiments for algorithms developed considering several instances presented in literature and others generated at random. These results, some of them compared with the literature, validate the approaches proposed and suggest their applicability to deal with practical situations involving the problems here investigatedDoutoradoDoutor em Ciência da Computaçã

Logic based Benders' decomposition for orthogonal stock cutting problems

We consider the problem of packing a set of rectangular items into a strip of fixed width, without overlapping, using minimum height. Items must be packed with their edges parallel to those of the strip, but rotation by 90\ub0 is allowed. The problem is usually solved through branch-and-bound algorithms. We propose an alternative method, based on Benders' decomposition. The master problem is solved through a new ILP model based on the arc flow formulation, while constraint programming is used to solve the slave problem. The resulting method is hybridized with a state-of-the-art branch-and-bound algorithm. Computational experiments on classical benchmarks from the literature show the effectiveness of the proposed approach. We additionally show that the algorithm can be successfully used to solve relevant related problems, like rectangle packing and pallet loading

Three-Dimensional Knapsack Problem with Pre-Placed Boxes and Vertical Stability

A three-dimensional knapsack problem packs a subset of rectangular boxes inside a bin with fixed size such that the total value of packed boxes is maximized. Each box has its own value and size and can be freely rotated into any of the six positions while its edges are parallel to the bin\u27s edges. A Mixed Integer Linear Programming is developed for the 3D knapsack problem, while some practical constraints such as vertical stability are considered. However, the given model can be applied to two dimensional problems as well. The proposed solution methodology is based on the sequence triple. Simulated annealing technique is used to model the heuristic approach. Moreover, the situation where some boxes are pre-placed in the bin is investigated. These pre-placed boxes represent potential obstacles. Numerical experiments are conducted for bins with and without obstacles. The results show that the heuristic approach is successful and can handle different kinds of instances

Problems, Models and Algorithms in One- and Two-Dimensional Cutting

Within such disciplines as Management Science, Information and Computer Science, Engineering, Mathematics and Operations Research, problems of cutting and packing (C&P) of concrete and abstract objects appear under various specifications (cutting problems, knapsack problems, container and vehicle loading problems, pallet loading, bin packing, assembly line balancing, capital budgeting, changing coins, etc.), although they all have essentially the same logical structure. In cutting problems, a large object must be divided into smaller pieces; in packing problems, small items must be combined to large objects. Most of these problems are NP-hard. Since the pioneer work of L.V. Kantorovich in 1939, which first appeared in the West in 1960, there has been a steadily growing number of contributions in this research area. In 1961, P. Gilmore and R. Gomory presented a linear programming relaxation of the one-dimensional cutting stock problem. The best-performing algorithms today are based on their relaxation. It was, however, more than three decades before the first `optimum? algorithms appeared in the literature and they even proved to perform better than heuristics. They were of two main kinds: enumerative algorithms working by separation of the feasible set and cutting plane algorithms which cut off infeasible solutions. For many other combinatorial problems, these two approaches have been successfully combined. In this thesis we do it for one-dimensional stock cutting and two-dimensional two-stage constrained cutting. For the two-dimensional problem, the combined scheme provides mostly better solutions than other methods, especially on large-scale instances, in little time. For the one-dimensional problem, the integration of cuts into the enumerative scheme improves the results of the latter only in exceptional cases. While the main optimization goal is to minimize material input or trim loss (waste), in a real-life cutting process there are some further criteria, e.g., the number of different cutting patterns (setups) and open stacks. Some new methods and models are proposed. Then, an approach combining both objectives will be presented, to our knowledge, for the first time. We believe this approach will be highly relevant for industry

Three-Dimensional Container Loading: A Simulated Annealing Approach

High utilization of cargo volume is an essential factor in the success of modern enterprises in the market. Although mathematical models have been presented for container loading problems in the literature, there is still a lack of studies that consider practical constraints. In this paper, a Mixed Integer Linear Programming is developed for the problem of packing a subset of rectangular boxes inside a container such that the total value of the packed boxes is maximized while some realistic constraints, such as vertical stability, are considered. The packing is orthogonal, and the boxes can be freely rotated into any of the six orientations. Moreover, a sequence triple-based solution methodology is proposed, simulated annealing is used as modeling technique, and the situation where some boxes are preplaced in the container is investigated. These preplaced boxes represent potential obstacles. Numerical experiments are conducted for containers with and without obstacles. The results show that the simulated annealing approach is successful and can handle large number of packing instances

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set