Made available in DSpace on 2016-06-02T19:51:39Z (GMT). No. of bitstreams: 1 2523.pdf: 1711552 bytes, checksum: cf13454170c0e1db1eb5ae2aa8cff6a3 (MD5) Previous issue date: 2009-02-26 / Financiadora de Estudos e Projetos / The object of this study is a particular case of the cutting and packing problems, known as container loading problems. These problems consist in arranging rectangular boxes orthogonally into containers (or into trucks, railcars and pallets), in order to optimize an objective function, for example, maximize the utilization of the available space, or minimize the number of the required containers to load all the available items. The objective of this study is to develop mathematical programming models to deal with situations commonly found in container loading practice. Multiple orientations of the boxes, weight limit of the container, cargo stability, load bearing strength of the boxes and multiple destinations of the cargo are considered. The author is not aware of mathematical formulations available in the cutting and packing literature that deal with such considerations, and this paper intends to contribute with possible formulations that describe these situations, although not very realistic for being used in practice. Computational experiments with the proposed models are performed with the software AMS/CPLEX and randomly generated instances extracted from the cutting and packing literature. The results show that the models are consistent and properly represent the practical situations treated, although this approach (in its current version) is limited to solve to optimality only medium-sized problems. However, we believe that the proposed models can be useful to motivate future research exploring decomposition methods, relaxations, heuristics, among others, to solve the present problems. / O objeto de estudo deste trabalho é um caso particular dos problemas de corte e empacotamento, conhecido como problemas de carregamento de contêineres. Estes problemas consistem em arranjar caixas retangulares ortogonalmente dentro de contêineres (ou caminhões, vagões ferroviários e paletes), de maneira a otimizar uma função objetivo, por exemplo, maximizar o aproveitamento do espaço disponível, ou então minimizar o número de contêineres necessários para carregar todas as caixas disponíveis. O objetivo deste trabalho é desenvolver modelos de programação matemática que abordem situações comumente encontradas na prática do carregamento de contêineres. Considerações de múltiplas orientações das caixas, limite de peso do contêiner, estabilidade do carregamento, resistência das caixas ao empilhamento e carga fracionada em múltiplos destinos são tratadas. O autor não tem conhecimento de formulações matemáticas disponíveis na literatura de corte e empacotamento que tratem estas considerações, e este trabalho pretende contribuir com possíveis formulações que, embora pouco realistas para serem aplicadas na prática, descrevem estas situações. Experimentos computacionais com os modelos propostos são realizados utilizando o aplicativo GAMS/CPLEX e exemplos gerados aleatoriamente e da literatura. Os resultados mostram que os modelos são coerentes e representam adequadamente as situações tratadas, embora esta abordagem (na sua versão atual) esteja limitada a resolver otimamente apenas problemas de tamanho bem moderado. No entanto, os modelos podem ser úteis para motivar pesquisas futuras explorando métodos de decomposição, métodos de relaxação, métodos heurísticos, entre outros, para resolver os problemas em questão.

Le problème de placement sur deux dimensions consiste à décider s’il existe un rangement d’objets rectangulaires dans une boîte donnée. C’est un problème combinatoire difficile (à la complexité du respect des capacités s’ajoute celle du positionnement des objets).Dans cette thèse, nous considérons les variantes sans rotation des objets et avec ou sansoptimisation de la valeur des objects placés.Nous menons une étude exploratoire des méthodologies qui peuvent être développéesà l’interface de la programmation mathématique, de l’optimisation combinatoire et de lathéorie des graphes. Notre objectif est aussi de développer des approches non basées surune discrétisation de la boîte, les plus performantes à l’heure actuelle.Dans ce mémoire, nous effectuons d’abord une étude théorique des qualités de bornesqui peuvent être obtenues avec les différentes formulations classiques. Au cours de cetteétude, nous renforçons certaines de ces formulations et en proposons de nouvelles formulations. Une étude qualitative des bornes issues de la relaxation linéaire des formulationstestés sur des jeux d’instances classiques de la littérature confirme l’étude théorique. Cetteétude permet de se rendre compte des facteurs déterminant la qualité des bornes et desenjeux à relever par la programmation mathématique.Par la suite, nous avons développé et testé deux approches de résolution innovantes.L’une est basée sur la décomposition de Dantzig-Wolfe associée à un branchement surles contraintes disjonctives de non recouvrement des objets. Cette approche a permis uneamélioration des résultats obtenus par la programmation mathématique.L’autre approche constitue en une approche combinatoire basée sur diverses caractérisations des graphes d’intervalles (modélisant le chevauchement des objets selon leurprojection sur chaque axe). Un premier algorithme est basé sur l’énumération de matricesde uns-consécutifs. Un autre utilise des arbres étiquetés pour éliminer plus efficacement lescas de symétries entre placements. Ces approches ont l’avantage de ne pas dépendre d’unediscrétisation du conteneur / The two dimensional orthogonal packing problem consists in deciding whether thereexists a packing of rectangular items in a given bin. This is a hard combinatorial problem(in addition to capacity constraints, one has to face the complexity of item positionning).In this thesis, we consider the case without item rotation and with or without packingvalue optimization.We explore methodologies at the interface of mathematical programming, combinatorial optimization and graph theory. Our aim is also to develop approaches not based on abin discretization (i.e. an alternative to such methods that are currently the most effective).In this work, we perform a theorical study of the quality of bounds of differents classicalformulations. We tighten some formulations and we propose new formulations. We perform a numerical study to test bound quality on classical instances. This study permits toidentify the determinant factor in the quality of mathematical programming formulations.We develop and test two resolution approaches. The first is based on Dantzig-Wolfedecomposition associated with a branching on no-overlapping disjunctive constraints. Thisapproach permits to improve results obtained by mathematical programming.The second approach establish a combinatorial approach based on multiple intervalgraph caracterization (modelling the item no-overlapping according to their projection oneach axis). The first algorithm is based on consecutive ones matrices enumeration. An otheruse labelled tree to eliminate more efficiently symmetry in packing. These approaches haveto advantage of being independent from bin discretization

Nesta tese abordamos o problema de empacotamento em faixas bidimensional em níveis - 2LSP. O 2LSP é um problema de otimização combinatória que, no que diz respeito a modelagem, tem recebido pouca atenção por parte da comunidade científica. Atualmente, o modelo mais competitivo para este problema, até onde sabemos, é o proposto por Lodi et al. em 2004, onde é acrescentado ao problema a restrição de que os itens devem ser alocados formando níveis. Em 2015, um modelo de fluxo para tratar o problema foi apresentado por Mehdi Mrad. A literatura apresenta alguns modelos matemáticos que, embora não seja especificamente para este problema, são modelos eficientes e podem ser adaptados para o 2LSP. Neste trabalho, desenvolvemos novos modelos para o problema, adaptando três modelos de programação linear inteira mista da literatura. Mais ainda, comparamos o desempenho computacional destes novos modelos com os modelos de Lodi et al. e de Mehdi Mrad, usando instâncias clássicas da literatura. Os resultados computacionais mostram que uma das novas formulações matemáticas supera os demais modelos em relação ao número de soluções ótimas. Para finalizar, apresentamos uma aplicação prática com a finalidade de desenvolver uma ferramenta para a geração automática dos planogramas utilizados para a montagem de gôndulas de supermercados. Para a aplicação, apresentamos um modelo de programação inteira mista preliminar que pode ser aplicado para tratar aplicações reais. / In this thesis we approached the two-dimensional level strip packing problem - 2LSP. 2LSP is a combinatorial optimization problem that, with respect to modeling, has received little attention from the scientific community. To the best of our knowledge, the most competitive model is the one proposed by Lodi et al. in 2004, where the items are packed by levels. In 2015, an arc flow model addressing the problem was proposed by Mehdi Mrad. The literature presents some mathematical models, despite not addressing specifically this problem, they are efficient and can be adapted for the two-dimensional level strip packing problem. In this thesis, we develop new models for the problem by adapting three mixed integer linear programming models from the literature. We also compare the computational performance of these new models with the models of Lodi et al. and Mehdi Mrad, by solving classical instances from the literature. The computational results show that one of the new mathematical formulations outperforms the remaining models with respect to the number of optimal solutions. To conclude, we present a practical application with the purpose of developing a tool for the automatic generation of the planograms used for the assembly of supermarket gondolas. For the application, we present a preliminary mixed integer programming model that can be applied to solve real applications.

Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2018-03-15T20:24:53Z No. of bitstreams: 2 Dissertação - Jéssica Gabriela de Almeida Cunha - 2018.pdf: 3483915 bytes, checksum: 12c37e736c4d6f53761fc0255e6bff6d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-03-16T11:10:21Z (GMT) No. of bitstreams: 2 Dissertação - Jéssica Gabriela de Almeida Cunha - 2018.pdf: 3483915 bytes, checksum: 12c37e736c4d6f53761fc0255e6bff6d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-03-16T11:10:21Z (GMT). No. of bitstreams: 2 Dissertação - Jéssica Gabriela de Almeida Cunha - 2018.pdf: 3483915 bytes, checksum: 12c37e736c4d6f53761fc0255e6bff6d (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-22 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / This work brings the use of grid of points in the resolution of cutting and packing problems that consider rectangular shaped items. The grids can be considered for mathematical programming models and heuristics, and they are independent of the problem. The following grids that are defined by the literature are considered for this work: canonical dissections (also known as normal patterns), reduced raster points, useful numbers, corner points, regular normal patterns, extreme points, and meet-in-the-middle patterns. The objective is to assess the influence of each grid on the resolution of cutting and packing problems, before and after applying reduction procedures, as the one related to update the items size. Theoretical results are obtained from relations of set and size between the grids, showing that the grid of normal patterns and useful numbers are equivalent and, thus, proving formally that the grid of reduced raster points ensures an optimal solution (this result has been formally opened in the literature). In addition, we propose a new procedure to reduce the size of grids. In order to validate the proposed procedure and evaluate the grids, we perform experiments over instances from the literature, where it is possible to observe that the grids of reduced raster points and meet-in-the-middle patterns are the smallest. Experiments were also conducted in a two-dimensional packing problem that uses an integer linear programming model to pack the items in points of a grid. The results indicate that using the reduction procedures it is possible to obtain optimal solutions quicker. / Este trabalho traz o uso de malhas de pontos na resolução de problemas de corte e empacotamento para itens com formato retangular. As malhas podem ser consideradas em modelos de programação matemática e heurísticas, sendo independentes do problema tratado. As seguintes malhas definidas pela literatura, canonical dissections (também conhecida por normal patterns), reduced raster points, useful numbers, corner points, regular normal patterns, extreme points e meet-in-the-middle patterns, são consideradas neste trabalho. O objetivo é apresentar relações que existem entre as malhas e analisar a influência delas sobre o tempo gasto na resolução de problemas de corte e empacotamento, antes e após aplicar procedimentos de redução, como atualizar o tamanho dos itens. Resultados teóricos são obtidos envolvendo relações de conjunto e tamanho entre as malhas, mostrando que a malha de normal patterns e useful numbers são equivalentes e, assim, permitindo provar formalmente que a malha de reduced raster points garante uma solução ótima (resultado que estava em aberto na literatura). Além disso, propõe-se um novo procedimento visando reduzir o tamanho das malhas. Como forma de validar o procedimento proposto e avaliar a redução que ele proporciona nas malhas, executam-se experimentos sobre instâncias da literatura, sendo possível observar que as malhas de reduced raster points e meet-in-the-middle patterns são as menores. Experimentos também foram realizados sobre um problema de empacotamento bidimensional que utiliza um modelo de programação linear inteira para empacotar os itens em pontos da malha. Os resultados indicam que utilizando os procedimentos de redução é possível obter soluções ótimas mais rapidamente.

Les travaux de thèse présentés s’intéressent à l’optimisation des systèmes hospitaliers. Une solution existante est la mutualisation de ressources au sein d’un même territoire. Cela peut passer par différentes formes de coopération dont la Communauté Hospitalière de Territoire. Différents problèmes sont définis en fonction du niveau de décision : stratégique, tactique ou opérationnel ; et du niveau de modélisation : macroscopique, mesoscopique et microscopique. Des problèmes de dimensionnement, de planification et d’ordonnancement peuvent être considérés. Nous définissons notamment le problème de planification d’activités avec affectation de ressources. Plusieurs cas sont dissociés : soit les ressources humaines sont à capacité infinie, soit elles sont à capacité limitée et leur affectation sur site est une donnée, soit elles sont à capacité limitée et leur affectation sur site est une variable. Ces problèmes sont spécifiés et formalisés mathématiquement. Tous ces problèmes sont comparés à un problème de bin packing : le problème du bin packing de base pour le problème où les ressources humaines sont à capacité infinie, le problème du bin packing avec interdépendances dans les deux autres cas. Le problème du bin packing avec incompatibilités est ainsi défini. De nombreuses méthodes de résolution ont déjà été proposées pour le problème du bin packing. Nous faisons plusieurs propositions dont un couplage hiérarchique entre une heuristique et une métaheuristique. Des métaheuristiques basées individu et une métaheuristique basée population, l’optimisation par essaim particulaire, sont utilisées. Cette proposition nécessite un nouveau codage inspiré des problèmes de permutation d’ordonnancement. Cette méthode donne de très bons résultats sur les instances du problème du bin packing. Elle est simple à appliquer : elle couple des méthodes déjà connues. Grâce au couplage proposé, les nouvelles contraintes à considérer nécessitent d’être intégrées uniquement au niveau de l’heuristique. Le fonctionnement de la métaheuristique reste le même. Ainsi, notre méthode est facilement adaptable au problème de planification d’activités avec affectation de ressources. Pour les instances de grande taille, le solveur utilisé comme référence ne donne qu’un intervalle de solutions. Les résultats de notre méthode sont une fois encore très prometteurs : les solutions obtenues sont meilleures que la borne supérieure retournée par le solveur. Il est envisageable d’adapter notre méthode sur d’autres problèmes plus complexes par intégration dans l’heuristique des nouvelles contraintes à considérer. Il serait notamment intéressant de tester ces méthodes sur de réelles instances hospitalières afin d’évaluer leur portée. / The presented work is about optimization of the hospital system. An existing solution is the pooling of resources within the same territory. This may involve different forms of cooperation between several hospitals. Various problems are defined at the decision level : strategic, tactical or operational ; and at the modeling level : macroscopic, mesoscopic and microscopic. Problems of sizing, planning and scheduling may be considered. We define the problem of activities planning with resource allocation. Several cases are dissociated : either human resources are under infinite capacity, or they are under limited capacity and their assignment on a place is given, or they are under limited capacity and their assignment is a variable. These problems are specified and mathematically formalized. All thes problems are compared to a bin packing problem : the classical problem of bin packing is used for the problem where human resources are under infinite capacity, the bin packing problem with interdependencies is used in the two other cases. The bin packing problem with incompatibilities is defined. Many resolution methods have been proposed for the bin packing problem. We make several propositions including a hierarchical coupling between heuristic and metaheuristic. Single based metaheuristics and a population based metaheuristic, the particle swarm optimization, are used. This proposition requires a new encoding inspired by permutation problems. This method gives very good results to solve instances of the bin packing problem. It is easy to apply : it combines already known methods. With the proposed coupling, the new constraints to be considered need to be integrated only on the heuristic level. The running of the metaheuristic is the same. Thus, our method is easily adaptable to the problem of activities planning with resource allocation. For big instances, the solver used as a reference returns only an interval of solutions. The results of our method are once again very promising : the obtained solutions are better than the upper limit returned by the solver. It is possible to adapt our method on more complex issues through integration into the heuristic of the new constraints to consider. It would be particularly interesting to test these methods on real hospital authorities to assess their significance.