167 research outputs found

    Arc flow formulations based on dynamic programming: Theoretical foundations and applications

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    Network flow formulations are among the most successful tools to solve optimization problems. Such formulations correspond to determining an optimal flow in a network. One particular class of network flow formulations is the arc flow, where variables represent flows on individual arcs of the network. For NP-hard problems, polynomial-sized arc flow models typically provide weak linear relaxations and may have too much symmetry to be efficient in practice. Instead, arc flow models with a pseudo-polynomial size usually provide strong relaxations and are efficient in practice. The interest in pseudo-polynomial arc flow formulations has grown considerably in the last twenty years, in which they have been used to solve many open instances of hard problems. A remarkable advantage of pseudo-polynomial arc flow models is the possibility to solve practical-sized instances directly by a Mixed Integer Linear Programming solver, avoiding the implementation of complex methods based on column generation. In this survey, we present theoretical foundations of pseudo-polynomial arc flow formulations, by showing a relation between their network and Dynamic Programming (DP). This relation allows a better understanding of the strength of these formulations, through a link with models obtained by Dantzig-Wolfe decomposition. The relation with DP also allows a new perspective to relate state-space relaxation methods for DP with arc flow models. We also present a dual point of view to contrast the linear relaxation of arc flow models with that of models based on paths and cycles. To conclude, we review the main solution methods and applications of arc flow models based on DP in several domains such as cutting, packing, scheduling, and routing

    2차원 2단계 배낭문제에 대한 정수계획모형 및 최적해법

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    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

    Pattern Generation for Three Dimensional Cutting Stock Problem

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    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.

    Two-dimensional placement compaction using an evolutionary approach: a study

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    The placement problem of two-dimensional objects over planar surfaces optimizing given utility functions is a combinatorial optimization problem. Our main drive is that of surveying genetic algorithms and hybrid metaheuristics in terms of final positioning area compaction of the solution. Furthermore, a new hybrid evolutionary approach, combining a genetic algorithm merged with a non-linear compaction method is introduced and compared with referenced literature heuristics using both randomly generated instances and benchmark problems. A wide variety of experiments is made, and the respective results and discussions are presented. Finally, conclusions are drawn, and future research is defined

    Models and Solutions of Resource Allocation Problems based on Integer Linear and Nonlinear Programming

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    In this thesis we deal with two problems of resource allocation solved through a Mixed-Integer Linear Programming approach and a Mixed-Integer Nonlinear Chance Constraint Programming approach. In the first part we propose a framework to model general guillotine restrictions in two dimensional cutting problems formulated as Mixed-Integer Linear Programs (MILP). The modeling framework requires a pseudo-polynomial number of variables and constraints, which can be effectively enumerated for medium-size instances. Our modeling of general guillotine cuts is the first one that, once it is implemented within a state of-the-art MIP solver, can tackle instances of challenging size. Our objective is to propose a way of modeling general guillotine cuts via Mixed Integer Linear Programs (MILP), i.e., we do not limit the number of stages (restriction (ii)), nor impose the cuts to be restricted (restriction (iii)). We only ask the cuts to be guillotine ones (restriction (i)). We mainly concentrate our analysis on the Guillotine Two Dimensional Knapsack Problem (G2KP), for which a model, and an exact procedure able to significantly improve the computational performance, are given. In the second part we present a Branch-and-Cut algorithm for a class of Nonlinear Chance Constrained Mathematical Optimization Problems with a finite number of scenarios. This class corresponds to the problems that can be reformulated as Deterministic Convex Mixed-Integer Nonlinear Programming problems, but the size of the reformulation is large and quickly becomes impractical as the number of scenarios grows. We apply the Branch-and-Cut algorithm to the Mid-Term Hydro Scheduling Problem, for which we propose a chance-constrained formulation. A computational study using data from ten hydro plants in Greece shows that the proposed methodology solves instances orders of magnitude faster than applying a general-purpose solver for Convex Mixed-Integer Nonlinear Problems to the deterministic reformulation, and scales much better with the number of scenarios

    Models and algorithms for hard optimization problems

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    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 new heuristic algorithm for two-dimensional defective stock guillotine cutting stock problem with multiple stock sizes

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    U radu se uglavnom raspravlja o problemu rezanja giljotinom dvodimenzijske oštećene robe raspoložive u različitim veličinama. Za raspravu o problemu predlaže se novi heuristički algoritam u obliku stabla. Takav se algoritam sastoji od dva dijela: prvi dio je početno rješenje problema rezanja robe kad ne postoje oštećenja robe; drugi dio je konačno rješenje optimizacije utemeljeno na prvom dijelu uz razmatranje oštećenja. U radu se također ocjenjuju rezultati predloženog algoritma. Eksperimentalnim se rezultatima demonstrira učinkovitost algoritma za problem rezanja dvodimenzijske oštećene robe i pokazuje da se algoritmom može poboljšati ne samo stopa iskoristivosti robe već i stopa ponovne uporabe ostataka smanjenjem fragmentacije ostataka.This paper mainly addresses a two-dimensional defective stocks guillotine cutting stock problem where stock of different sizes is available. Herein a new heuristic algorithm which is based on tree is proposed to discuss this problem. In particular, such an algorithm consists of two parts: the first part is an initial solution of the cutting stock problem where there are no defects on the stocks; the second part is the final optimization solution which is set up on the basis of the first part and takes the defects into consideration. This paper also evaluates the performance of the proposed algorithm. The experimental results demonstrate the effectiveness of the algorithm for the two-dimensional defective stocks cutting stock problem and show that the algorithm can improve not only the utilization rate of stocks, but also the reuse rate of remainders by reducing the fragmentation of remainders
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