Bin Packing and Related Problems: General Arc-flow Formulation with Graph Compression

We present an exact method, based on an arc-flow formulation with side constraints, for solving bin packing and cutting stock problems --- including multi-constraint variants --- by simply representing all the patterns in a very compact graph. Our method includes a graph compression algorithm that usually reduces the size of the underlying graph substantially without weakening the model. As opposed to our method, which provides strong models, conventional models are usually highly symmetric and provide very weak lower bounds. Our formulation is equivalent to Gilmore and Gomory's, thus providing a very strong linear relaxation. However, instead of using column-generation in an iterative process, the method constructs a graph, where paths from the source to the target node represent every valid packing pattern. The same method, without any problem-specific parameterization, was used to solve a large variety of instances from several different cutting and packing problems. In this paper, we deal with vector packing, graph coloring, bin packing, cutting stock, cardinality constrained bin packing, cutting stock with cutting knife limitation, cutting stock with binary patterns, bin packing with conflicts, and cutting stock with binary patterns and forbidden pairs. We report computational results obtained with many benchmark test data sets, all of them showing a large advantage of this formulation with respect to the traditional ones

Pattern Generation for Three Dimensional Cutting Stock Problem

We consider the problem of three-dimensional cutting of a large block that is to be cut into some small block pieces, each with a specific size and request. Pattern generation is an algorithm that has been used to determine cutting patterns in one-dimensional and two-dimensional problems. The purpose of this study is to modify the pattern generation algorithm so that it can be used in three-dimensional problems, and can determine the cutting pattern with the minimum possible cutting residue. The large block will be cut based on the length, width, and height. The rest of the cuts will be cut back if possible to minimize the rest. For three-dimensional problems, we consider the variant in which orthogonal rotation is allowed. By allowing the remainder of the initial cut to be rotated, the dimensions will have six permutations. The result of the calculation using the pattern generation algorithm for three-dimensional problems is that all possible cutting patterns are obtained but there are repetitive patterns because they suggest the same number of cuts.

2차원 2단계 배낭문제에 대한 정수계획모형 및 최적해법

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 산업공학과, 2021. 2. 이경식.In this thesis, we study integer programming models and exact algorithms for the two-dimensional two-staged knapsack problems, which maximizes the profit by cutting a single rectangular plate into smaller rectangular items by two-staged guillotine cuts. We first introduce various integer programming models, including the strip-packing model, the staged-pattern model, the level-packing model, and the arc-flow model for the problem. Then, a hierarchy of the strength of the upper bounds provided by the LP-relaxations of the models is established based on theoretical analysis. We also show that there exists a polynomial-size model that has not been proven yet as far as we know. Exact methods, including branch-and-price algorithms using the strip-packing model and the staged-pattern model, are also devised. Computational experiments on benchmark instances are conducted to examine the strength of upper bounds obtained by the LP-relaxations of the models and evaluate the performance of exact methods. The results show that the staged-pattern model gives a competitive theoretical and computational performance.본 논문은 2단계 길로틴 절단(two-staged guillotine cut)을 사용하여 이윤을 최대화하는 2차원 2단계 배낭 문제(two-dimensional two-staged knapsack problem: 이하 2TDK)에 대한 정수최적화 모형과 최적해법을 다룬다. 우선, 본 연구에서는 스트립패킹모형, 단계패턴모형, 레벨패킹모형, 그리고 호-흐름모형과 같은 정수최적화 모형들을 소개한다. 그 뒤, 각각의 모형의 선형계획완화문제에 대해 상한강도를 이론적으로 분석하여 상한강도 관점에서 모형들 간 위계를 정립한다. 또한, 본 연구에서는 2TDK의 다항크기(polynomial-size) 모형의 존재성을 처음으로 증명한다. 다음으로 본 연구는 2TDK의 최적해를 구하는 알고리즘으로써 패턴기반모형들에 대한 분지평가 알고리즘과 레벨패킹모형을 기반으로 한 분지절단 알고리즘을 제안한다. 단계패턴모형이 이론적으로도 가장 좋은 상한강도를 보장할 뿐만 아니라, 계산 분석을 통해 단계패턴모형을 기반으로 한 분지평가 알고리즘이 제한된 시간 내 좋은 품질의 가능해를 찾음을 확인하였다.Abstract i Contents iv List of Tables vi List of Figures vii Chapter 1 Introduction 1 1.1 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . 8 Chapter 2 Integer Programming Models for 2TDK 9 2.1 Pattern-based Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Arc-flow Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.3 Level Packing Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 3 Theoretical Analysis of Integer Programming Models 20 3.1 Upper Bounds of AF and SM(1;1) . . . . . . . . . . . . . . . . . . 20 3.2 Upper Bounds of ML, PM(d), and SM(d; d) . . . . . . . . . . . . . . 21 3.3 Polynomial-size Model . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Chapter 4 Exact Methods 33 4.1 Branch-and-price Algorithm for the Strip Packing Model . . . . . . . 34 4.2 Branch-and-price Algorithm for the Staged-pattern Model . . . . . . 39 4.2.1 The Standard Scheme . . . . . . . . . . . . . . . . . . . . . . 39 4.2.2 The Height-aggregated Scheme . . . . . . . . . . . . . . . . . 40 4.3 Branch-and-cut Algorithm for the Modified Level Packing Model . . 44 Chapter 5 Computational Experiments 46 5.1 Instances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.2 Upper Bounds Comparison . . . . . . . . . . . . . . . . . . . . . . . 49 5.2.1 A Group of Small Instances . . . . . . . . . . . . . . . . . . . 49 5.2.2 A Group of Large Instances . . . . . . . . . . . . . . . . . . . 55 5.2.3 Class 5 Instances . . . . . . . . . . . . . . . . . . . . . . . . . 61 5.3 Solving Instances to Optimality . . . . . . . . . . . . . . . . . . . . . 65 5.3.1 A Group of Small Instances . . . . . . . . . . . . . . . . . . . 65 5.3.2 A Group of Large Instances . . . . . . . . . . . . . . . . . . . 69 5.3.3 Class 5 Instances . . . . . . . . . . . . . . . . . . . . . . . . . 72 Chapter 6 Conclusion 77 Bibliography 79 국문초록 83Maste

An Improved Arcflow Model for the Skiving Stock Problem

Because of the sharp development of (commercial) MILP software and hardware components, pseudo-polynomial formulations have been established as a viable tool for solving cutting and packing problems in recent years. Constituting a natural (but independent) counterpart of the well-known cutting stock problem, the one-dimensional skiving stock problem (SSP) asks for the maximal number of large objects (specified by some threshold length) that can be obtained by recomposing a given inventory of smaller items. In this paper, we introduce a new arcflow formulation for the SSP applying the idea of reflected arcs. In particular, this new model is shown to possess significantly fewer variables as well as a better numerical performance compared to the standard arcflow formulation

Evaluation of Procurement Scenarios in One-Dimensional Cutting Stock Problem with a Random Demand Mix

The one-dimensional cutting stock problem describes the problem of cutting standard length stock material into various specified sizes while minimizing the material wasted (the remnant or drop as manufacturing terms). This computationally complex optimization problem has many manufacturing applications. One-dimensional cutting stock problems arise in many domains such as metal, paper, textile, and wood. To solve it, the problem is formulated as an integer linear model first, and then solved using a common optimizer software. This paper revisits the stochastic version of the problem and proposes a priority-based goal programming approach. Monte Carlo simulation is used to simulate several likely inventory order policies to minimize the total number of shortages, overages, and the number of stocks carried in inventory

Improved flow-based formulations for the skiving stock problem

Thanks to the rapidly advancing development of (commercial) MILP software and hardware components, pseudo-polynomial formulations have been established as a powerful tool for solving cutting and packing problems in recent years. In this paper, we focus on the one-dimensional skiving stock problem (SSP), where a given inventory of small items has to be recomposed to obtain a maximum number of larger objects, each satisfying a minimum threshold length. In the literature, different modeling approaches for the SSP have been proposed, and the standard flow-based formulation has turned out to lead to the best trade-off between efficiency and solution time. However, especially for instances of practically meaningful sizes, the resulting models involve very large numbers of variables and constraints, so that appropriate reduction techniques are required to decrease the numerical efforts. For that reason, this paper introduces two improved flow-based formulations for the skiving stock problem that are able to cope with much larger problem sizes. By means of extensive experiments, these new models are shown to possess significantly fewer variables as well as an average better computational performance compared to the standard arcflow formulation

Novel approaches to container loading: from heuristics to hybrid tabu search

A thesis submitted for the degree of Doctor of Philosophy of the University ofBedford shireThis work investigates new approaches to the container loading problem which address the issue of how to load three-dimensional, rectangular items (e.g. boxes) into the container in such a way that maximum utilisation is made of the container space. This problem occurs in several industry sectors where the loading approach places cargo effectively into aeroplanes, ships, trailers or trucks in order to save considerable cost. In carrying out this work, the investigation starts by developing a new heuristic approach to the two-dimensional bin packing problem, which has lower complexity than container loading in the aspects of constraints and geometry. A novel approach, including the heuristic strategies and handling method for remaining areas, is developed that can produce good results when testing with benchmark and real world data. Based on the research for two-dimensional bin packing, a novel heuristic approach is developed to deal with the container loading problem with some practical constraints. The heuristic approach to container loading also includes heuristic strategies and the handling of remaining spaces. The heuristic strategies construct effective loading arrangements where combinations of identical or different box types are loaded in blocks. The handling method for remaining spaces further improves the loading arrangements through the representation, partitioning and merging of remaining spaces. The heuristic approach obtains better volume utilisation and the highest stability compared with other published heuristic approaches. However, it does not achieve as high a volume utilisation as metaheuristic approaches, e.g. genetic algorithms and tabu search.To improve volume utilisation, a new hybrid heuristic approach to the container loading problem is further developed based on the tabu search technique which covers the encoding, evaluation criterion and configuration of neighbourhood and candidate solutions. The heuristic strategies as well as the handling method for remaining spaces developed in the heuristic approach are used in this new hybrid tabu search approach. It is shown that the hybrid approach has better volume utilisation than the published approaches under the condition that all loaded boxes with one hundred per cent support from below. In addition, the experimental results show that both the heuristic and hybrid tabu search approaches can also be applied to the multiple container loading problem

Models and algorithms for hard optimization problems

This thesis is devoted to exact solution methods for NP-hard integer programming models. We consider two of these problems, the cutting stock problem and the vehicle routing problem. Both problems have been studied for several decades by researchers and practitioners of the Operations Research eld. Their interest and contribution to real-world applications in business, industry and several kinds of organizations are irrefutable. Our solution approaches are always exact. We contribute with new lower bounds, families of valid inequalities, integer programming models and exact algorithms for the problems we explore. More precisely, we address two variants of each of the referred problems. In what concerns cutting stock problems, we analyze the one-dimensional pattern minimization problem and the two-dimensional cutting stock problem with the guillotine constraint. The one-dimensional pattern minimization problem is a cutting and packing problem that becomes relevant in situations where changing from one pattern to another involves, for example, a cost for setting up the cutting machine. It is the problem of minimizing the number of di erent patterns of a given cutting stock solution. For this problem, we contribute with new lower bounds. The two-dimensional cutting stock problem with the guillotine constraint and two stages is also addressed. We propose a pseudo-polynomial network ow model, along with some reduction criteria to reduce its symmetry. We strengthen the model with a new family of cutting planes and propose a new lower bound. For this variant, we also consider some variations of the problem.Regarding vehicle routing problems, we address the vehicle routing problem with time windows and multiple use of vehicles and the location routing problem, with capacitated vehicles and depots and multiple use of vehicles. The rst of these problems considers the well know case of vehicle routing with time windows with the additional consideration that vehicles can be assigned to several routes within the same planning period. The second variant considers the combination of the rst problem, without time windows, with a location problem. This means that the depots to be used must be selected from a set of available ones. For both of these variants, we propose a network ow model whose nodes of the underlying graph correspond to time instants of the planning period and whose arcs correspond to vehicle routes. We reduce their symmetry by deriving several reduction criteria. For the vehicle routing problem with time windows and multiple use of vehicles, we propose an iterative algorithm to solve the problem exactly. Our proposed procedures are tested and compared with other methods from the literature. All the computational results produced by the series of experiments are presented and discussed.Esta tese e dedicada a métodos de resolução exata para problemas de programação inteira NP-difíceis. São considerados dois desses problemas, nomeadamente o problema de corte e empacotamento e o problema de encaminhamento de veículos. Ambos os problemas têm vindo a ser abordados por investigadores e profissionais da área da Investigação Operacional há já várias décadas. O seu interesse e contribuição para aplicações reais do mundo dos negócios e industria, assim como para inúmeros outros tipos de organizações são, hoje em dia, inegáveis. A nossa abordagem para a resolução dos problemas descritos e exata. Contribuímos com novos limites inferiores, novas famílias de desigualdades validas, novos modelos de programação inteira e algoritmos de resolução exata para os problemas que nos propomos explorar. Em particular, abordamos duas variantes de cada um dos referidos problemas. Em relação ao problema de corte e empacotamento, analisamos o problema de minimização de padrões a uma dimensão e o problema de corte e empacotamento a duas dimensões, com restrição de guilhotina. O problema de minimização de padrões a uma dimensão e pertinente em situações em que a mudança de padrão envolve, por exemplo, custos de reconfiguração nas máquinas de corte. E o problema de minimização do numero de padrões diferentes de uma dada solução de um problema de corte. Para este problema contribuímos com novos limites inferiores. O problema de corte e empacotamento a duas dimensões com restrição de guilhotina e dois estágios e também abordado. Propomos um modelo pseudopolinomial de rede de fluxos, assim como critérios de redução que eliminam parte da sua simetria. Reforçamos o modelo com uma nova família de planos de corte e propomos novos limites inferiores. Para esta variante, consideramos também outras variações do problema original. No que se refere ao problema de encaminhamento de veículos, abordamos um problema de encaminhamento de veículos com janelas temporais e múltiplas viagens, e também um problema de localização e encaminhamento de veículos com capacidades nos veículos e depósitos e múltiplo uso dos veículos. O primeiro destes problemas considera o conhecido caso de encaminhamento de veículos com janelas temporais, com a consideração adicional de que os veículos podem ser alocados a v arias rotas no decurso do mesmo período de planeamento. A segunda variante considera a combinação do primeiro problema, embora sem janelas temporais, com um problema de localização. Isto significa que os depósitos a usar são selecionados de um conjunto de localizações disponíveis. Para ambas as variantes, propomos um modelo pseudo-polinomial de rede de fluxos cujos nodos do grafo correspondente representam instantes de tempo do período de planeamento, e cujos arcos representam rotas. Derivamos critérios de redução com o intuito de reduzir a simetria. Para o problema com janelas temporais e múltiplas viagens, propomos um algoritmo iterativo que o resolve de forma exata. Os procedimentos propostos são testados e comparados com outros métodos da literatura. Todos os resultados obtidos pelas experiencias computacionais são apresentados e discutidos

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