University, Diss., 2003--Kiel.

The optimization of package selection in logistics, particularly within the realm of e-commerce, offers numerous potential advantages, such as a reduction in environmental impact and decreased costs. This thesis addresses the problem of allocating items to the minimum number of packages, known as the bin packing problem, by proposing various heuristics. We develop and assess heuristics for assigning products to groups, while heuristics for accommodating these groups within packages are derived from previous research. These heuristics are evaluated within a commercial context, taking into account factors such as delivery cost, environmental impact, and their applicability in real-time systems. Our findings indicate that optimal solutions for smaller orders can be ascertained within a reasonable timeframe, while even rudimentary heuristics yield satisfactory results. It was determined that a key attribute of an effective solution was lowering the number of packages used, as this correlates with reduced shipping costs and environmental impact.

Os problemas de corte e empacotamento são muito comuns nas indústrias e na logística. Dado um conjunto de N itens com diferentes pesos e um conjunto de M contentores com capacidade C, o problema de empacotamento unidimensional consiste em determinar o menor número de contentores a serem utilizados para alocar todos os itens respeitando a restrição de capacidade dos contentores. Nesse estudo pretende-se resolver o problema com instâncias benchmark da literatura, por meio de sessenta heurísticas diferentes, que são comparadas a quatro limitantes inferiores propostos na literatura com o intuito de avaliar a qualidade da solução heurística. Quatro limitantes inferiores e dez heurísticas construtivas diferentes foram programados em C++ num mesmo ambiente computacional, permitindo sua comparação tanto em termos de qualidade das soluções, quanto em termos dos tempos de processamento. Uma heurística simples de troca de itens entre contentores chamada Diferença-de-Quadrados foi proposta para melhorar as soluções iniciais do problema. A metaheurística simulated annealing foi acionada para melhorar a solução inicial quando o limitante inferior não foi atingido. Os parâmetros dos simulated annealing foram determinados com os dados das instâncias de forma diferente da utilizada na literatura. As combinações entre as dez soluções iniciais, a heurística Diferença-de-Quadrados e o simulated annealing geraram um conjunto de sessenta heurísticas diferentes. Os resultados mostraram que o algoritmo proposto é eficiente para resolver o problema com tempos de processamento adequados a tomada de decisão. / Cutting and packing problems are very common in industries and logistics. Given a set of N items with different weights and a set of M bins with full capacity C, the one-dimensional bin packing problem consists of determining the smallest number of bins capable to allocate all items respecting the capacity constraint of the bins. that impose that the sum of the weights of the items allocated to the bin is less than or equal to their capacity. In this study we intend to solve the problem with benchmark instances of the literature, by means of sixty different heuristics, which are compared to four lower bounds proposed in the literature in order to evaluate the quality of the heuristic solution. Four lower bounds and ten different constructive heuristics were programmed in C++ in the same computational environment, allowing their comparison both in terms of the quality of the solutions and in terms of processing times. A simple heuristic of item exchange between bins called Difference-of-Squares was proposed to improve the initial solutions of the problem. The simulated annealing metaheuristic was triggered to improve the initial solution when the lower bounds was not reached. The parameters of the simulated annealing were determined with the data of the instances differently from that used in the literature. The combinations of the ten initial solutions, the Difference-of-Squares heuristic and the simulated annealing generated a set of sixty different heuristics. The results showed that the proposed algorithm is efficient to solve the problem with adequate processing times for decision making.

Os problemas de corte e empacotamento são muito comuns nas indústrias e na logística. Dado um conjunto de N itens com diferentes pesos e um conjunto de M contentores com capacidade C, o problema de empacotamento unidimensional consiste em determinar o menor número de contentores a serem utilizados para alocar todos os itens respeitando a restrição de capacidade dos contentores. Nesse estudo pretende-se resolver o problema com instâncias benchmark da literatura, por meio de sessenta heurísticas diferentes, que são comparadas a quatro limitantes inferiores propostos na literatura com o intuito de avaliar a qualidade da solução heurística. Quatro limitantes inferiores e dez heurísticas construtivas diferentes foram programados em C++ num mesmo ambiente computacional, permitindo sua comparação tanto em termos de qualidade das soluções, quanto em termos dos tempos de processamento. Uma heurística simples de troca de itens entre contentores chamada Diferença-de-Quadrados foi proposta para melhorar as soluções iniciais do problema. A metaheurística simulated annealing foi acionada para melhorar a solução inicial quando o limitante inferior não foi atingido. Os parâmetros dos simulated annealing foram determinados com os dados das instâncias de forma diferente da utilizada na literatura. As combinações entre as dez soluções iniciais, a heurística Diferença-de-Quadrados e o simulated annealing geraram um conjunto de sessenta heurísticas diferentes. Os resultados mostraram que o algoritmo proposto é eficiente para resolver o problema com tempos de processamento adequados a tomada de decisão. / Cutting and packing problems are very common in industries and logistics. Given a set of N items with different weights and a set of M bins with full capacity C, the one-dimensional bin packing problem consists of determining the smallest number of bins capable to allocate all items respecting the capacity constraint of the bins. that impose that the sum of the weights of the items allocated to the bin is less than or equal to their capacity. In this study we intend to solve the problem with benchmark instances of the literature, by means of sixty different heuristics, which are compared to four lower bounds proposed in the literature in order to evaluate the quality of the heuristic solution. Four lower bounds and ten different constructive heuristics were programmed in C++ in the same computational environment, allowing their comparison both in terms of the quality of the solutions and in terms of processing times. A simple heuristic of item exchange between bins called Difference-of-Squares was proposed to improve the initial solutions of the problem. The simulated annealing metaheuristic was triggered to improve the initial solution when the lower bounds was not reached. The parameters of the simulated annealing were determined with the data of the instances differently from that used in the literature. The combinations of the ten initial solutions, the Difference-of-Squares heuristic and the simulated annealing generated a set of sixty different heuristics. The results showed that the proposed algorithm is efficient to solve the problem with adequate processing times for decision making.

Orientador: Rubén Augusto Romero Lázaro / Resumo: Neste trabalho apresenta-se uma nova meta-heurística, o Algoritmo Genético Evolucionário Especializado (AGE-E) para resolver uma das categorias dos Problemas de Carregamento de Contêiners, objeto de estudo que pertence à otimização, na Pesquisa Operacional. Considera-se a existência de múltiplos contêiners de iguais dimensões que permitem o carregamento completo da carga disponível em um contexto de transporte industrial. Esta carga é composta por caixas de sortimento fortemente hete-rogêneo e que permite a rotação em qualquer dasseis possibilidades, tornando o problema ainda mais complexo, e, porisso,menos estudado na literatura. Uma revisão bibliográfica é também apresentada, contendo uma visão geral das classificações do problema e, em particular, um estudo aprofundado sobre algoritmos genéticos. A implementação do AGE-E foi realizada, e os resultados computacionais foram comparados com as melhores soluções já apresentadas na literatura, demonstrando o potencial do AGE-E para estudosfuturos. / Doutor

Submitted by BRUNA DE LIMA ALCANTARA KITAMURA null (brunakitamura@yahoo.com.br) on 2017-10-30T20:10:34Z No. of bitstreams: 1 TESE-FINAL-BRUNA-G-LIMA.pdf: 4015697 bytes, checksum: cb6eb178262689807dbc777ab5d4d4dd (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-11-09T18:45:51Z (GMT) No. of bitstreams: 1 lima_bg_dr_ilha.pdf: 4015697 bytes, checksum: cb6eb178262689807dbc777ab5d4d4dd (MD5) / Made available in DSpace on 2017-11-09T18:45:51Z (GMT). No. of bitstreams: 1 lima_bg_dr_ilha.pdf: 4015697 bytes, checksum: cb6eb178262689807dbc777ab5d4d4dd (MD5) Previous issue date: 2017-09-06 / Neste trabalho apresenta-se uma nova meta-heurística, o Algoritmo Genético Evolucionário Especializado (AGE-E) para resolver uma das categorias dos Problemas de Carregamento de Contêiners, objeto de estudo que pertence à otimização, na Pesquisa Operacional. Considera-se a existência de múltiplos contêiners de iguais dimensões que permitem o carregamento completo da carga disponível em um contexto de transporte industrial. Esta carga é composta por caixas de sortimento fortemente hete-rogêneo e que permite a rotação em qualquer dasseis possibilidades, tornando o problema ainda mais complexo, e, porisso,menos estudado na literatura. Uma revisão bibliográfica é também apresentada, contendo uma visão geral das classificações do problema e, em particular, um estudo aprofundado sobre algoritmos genéticos. A implementação do AGE-E foi realizada, e os resultados computacionais foram comparados com as melhores soluções já apresentadas na literatura, demonstrando o potencial do AGE-E para estudosfuturos. / This work presents a new meta-heuristic, the Specialized Evolutionary Genetic Algorithm (AGE-E), which solves one of the categories of Container Loading Problems, object of study that belongs to Optimization, within the Operational Research. It’s considered the existence of multiple containers ofthe equal dimensionsthat promote the full loading of the availablecargoinindustrial transportation context. Thisload is composed ofstrongly heterogeneous assortment to the boxes, and allows rotation in any of the six possibilities, making the problem even more complex, and therefore less studied in the literature. A bibliographic review is also presented, containing an overview of the classifications of the problem and, in particular, an deepened study on genetic algorithms. The implementation of AGE-E was performed, and the computational results were compared with the best solutions already determined by the bibliography, demonstrating the potentialofAGE-E for future studies.

Denna rapport behandlar kandidatprojektet Optily som utförts av 8 studenter på Tekniska högskolan vid Linköpings universitet. Hela processen från planering och utveckling till resultatet av den slutgiltiga produkten presenteras och diskuteras. Även erfarenheter som fångats upp av projektgruppen under denna process behandlas. Företaget Ionbond Sweden AB, som är kund i projektet, arbetar med ytbeläggning av rundskaftade föremål. För att underlätta planeringen av hur deras beläggningskammare ska packas har ett datorprogram kallat Optily utvecklats av projektgruppen. Detta har med framgång ökat effektiviteten i packningen av maskinerna vilket leder till ökad omsättning eftersom fler föremål kan köras tillsammans. Utöver ökad omsättning bidrar detta också till att hjälpa Ionbond Sweden AB att nå sina uppsatta miljömål. Programmet har även lyckats förbättra arbetssituationen för de anställda genom att på förhand visa hur maskinerna ska packas och vilka ordrar som då kommer få plats. Genom att integrera systemet med Ionbond Sweden AB:s nuvarande produktdatabas hanteras alla olika produkter som kan behöva ytbeläggas. Packningens utformning tas sedan fram genom att placera objekten med hjälp av en optimeringsalgoritm vilken når ett resultat som konsekvent är bättre än vad planeringsansvarig tidigare lyckats med. Resultatet av optimeringen visualiseras sedan med hjälp av en schematisk bild på hur objekten ska placeras i beläggningskammaren för att på bästa sätt utnyttja den tillgängliga volymen.

Various types of transportation issues are a common practice. The issue may be approached mainly as the distribution of products from suppliers to consumers while minimising distribution costs. The difference of real transportation issues predominantly relates to the considered restrictions, such as capacities of vehicles and orders, time windows and other special distribution restrictions. Transportation issues were already defined by F.L. Hitchcock in 1941 and since then, a wide range of stochastic and non- determinist methods providing solutions to transportation issues have been developed. Nevertheless, introducing distribution restrictions in resolving real-life problems makes it difficult for such methods to be applied. This thesis provides a compilation of the well-known determinist methods that may be used to resolve transportation issues. The methods that are appropriate for resolving real issues are discussed in more detail. The solution procedure of the selected method is demonstrated using simple examples and the results are compared with the results of other methods. An analysis of the above methods is used to design and implement new methods to resolve real transportation issues, their results being compared with the methods provided by the commercial software product.

Problemas de corte e empacotamento de itens irregulares são problemas que visam determinar um leiaute ótimo de objetos pequenos dentro de objetos maiores, a fim de atender a uma demanda. Estes problemas têm grande importância prática, já que surgem em vários tipos de indústria (como a têxtil, a de móveis e a de calçados). O problema estudado neste trabalho é o problema de corte de itens irregulares em recipientes. Os recipientes são delimitados e o objetivo é encontrar um leiaute dos objetos menores, sem sobreposição, dentro dos objetos maiores utilizando a menor quantidade de recipientes. Propomos um novo método de resolução para o problema. Nosso método é um algoritmo que gerencia um conjunto de heurísticas, de baixo nível, específicas para a resolução do problema com recipientes retangulares e irregulares. Recipientes irregulares são polígonos convexos e não convexos, que podem ser furados. As heurísticas desenvolvidas utilizam uma malha de pontos sobre a técnica de no-fit polygon para evitar a sobreposição dos itens e encontrar posições viáveis no recipiente retangular ou irregular. Os experimentos computacionais foram feitos para um grande conjunto de instâncias, de recipientes retangulares e irregulares. Os resultados demonstram a competitividade do método, que obtêm resultados bons e algumas soluções ótimas, em um tempo computacional aceitável. / Cutting and packing of irregular items are problems that aim to determine the optimum layout of small objects within larger objects (that we call bins), in order to meet a demand. These problems have great practical importance, since they emerge in various types of industry (such as textile, furniture and shoemaking). The problem studied in this work is the irregular bin packing problem. The bins are enclosed and the goal is to find a layout of items, without overlap, within the bins by using the minimum quantity of them. We propose a new method of resolution to this problem. Our method is an algorithm that manages a set of low-level heuristics, specific to solve the problem with rectangular bins and irregular bins. Irregular bins are convex and non-convex polygons, which may contain holes. The developed heuristics uses a mesh of points and the technique of no-fit polygon to avoid the overlapping of items and find feasible positions in rectangular or irregular bins. The computational experiments were performed for a large set of instances, using both rectangular and irregular bins. The results demonstrate the competitiveness of the method, which can get good results and some optimal solutions within an acceptable computational time.

Cette thèse a été réalisée dans le cadre du projet « Gestion et Optimisation de la Chaîne Documentaire », projet labellisé par le Pôle de compétitivité des Industries du Commerce. Le projet a pour but de concevoir et de développer un nouveau workflow et un outil d’aide à la décision. Ce système doit être capable de gérer et d’optimiser le flux complet dématérialisé de contrats reçus à COFIDIS.Nous présentons d’abord le framework retenu dans le cadre du projet pour modéliser et implémenter le workflow. En phase de conception BPMN a été choisi. Pour la partie développement, l’utilisation de BPEL a été préconisée pour implémenter et exécuter l'application finale (services web).Cependant la flexibilité offerte par BPMN peut conduire à des propriétés indésirables du processus telles que blocage et inaccessibilité. De plus, BPMN a été conçu pour fournir des modèles Orientés Process. Les données ou les ressources y sont donc peu représentées. En conséquence, l'analyse de performance sur un modèle BPMN est quasi inexistante.Afin de surmonter ces problèmes nous proposons d’insérer dans le framework deux nouvelles phases. Ces deux phases sont appliquées au modèle BPMN. La première est une phase de vérification et de validation et la deuxième une phase d'optimisation. Ces deux phases sont réalisées en transformant le modèle BPMN vers un langage formel. Notre choix dans ce travail a été d'utiliser les réseaux de Petri. Ce qui nous a permis de vérifier et de valider de bonnes propriétés du process. Quant à l’optimisation, nous avons défini une nouvelle variante du problème d’affectation (bin packing problem) et proposé une résolution à intégrer dans le processus d’aide à la décision / This thesis has been realized as a part of the project GOCD (French acronym for Management and optimization of document life cycle) and within the context of the French competitive cluster PICOM. The project aims to design and develop a new paperless workflow system and decision making tool to replace the current paper based system. The new workflow system must manage and optimize received credit demands at COFIDIS.The first part of this thesis presents and discusses a framework to model and implement workflow systems. The proposed framework allows more flexibility in workflow reengineering process and operational analysis for different business process. The proposed framework uses the most recent and promising language to model and execute workflow the Business Process Modeling Notation (BPMN) and Business Process Execution Language (BPEL).The flexibility offered by BPMN can also lead to undesirable properties for business process such as deadlocks and unreachablity. More, BPMN notation was designed to model business process, and little consideration was concentrated to represent data and resources. As a result, carrying out performance analysis on a BPMN model is also limited.To overcome these problems, we propose two additional phases in the reengineering process. They are applied to the target BPMN model. The first phase is verification and validation and the second one is optimization. These two phases are realized by transforming the BPMN model to a formal language, Petri nets. As for optimization, a new variant of bin packing problem has been defined. And we propose to integrate its resolution in a decision making tool