Avec la forte croissance du e-commerce et l'augmentation continue de la population des villes impliquant des niveaux de congestion plus élevés, les réseaux de distribution doivent déployer des échelons supplémentaires pour offrir un ajustement dynamique aux besoins des entreprises au cours du temps et faire face aux aléas affectant l’activité de distribution. Dans ce contexte, les praticiens s'intéressent aux réseaux de distribution à deux échelons. Dans cette thèse, nous commençons par présenter une revue complète des problèmes de design des réseaux de distribution et souligner des caractéristiques essentielles de modélisation. Ces aspects impliquent la structure à deux échelons, l’aspect multi-période, l’incertitude et les méthodes de résolution. Notre objectif est donc, d’élaborer un cadre complet pour le design d’un réseau de distribution efficace à deux échelons, sous incertitude et multi-périodicité, dans lequel les produits sont acheminés depuis les plateformes de stockage (WP) vers les plateformes de distribution (DP) avant d'être transportés vers les clients. Ce cadre est caractérisé par une hiérarchie temporelle entre le niveau de design impliquant des décisions relatives à la localisation des plateformes et à la capacité allouée aux DPs sur une échelle de temps annuelle, et le niveau opérationnel concernant des décisions journalières de transport. % sur une base journalière.Dans une première étude, nous introduisons le cadre complet pour le problème de design de réseaux de distribution à deux échelons avec une demande incertaine, une demande et un coût variables dans le temps. Le problème est formulé comme un programme stochastique à plusieurs étapes. Il implique au niveau stratégique des décisions de localisation des DPs ainsi que des décisions d'affectation des capacités aux DPs sur plusieurs périodes de design, et au niveau opérationnel des décisions de transport sous forme d'arcs origine-destination. Ensuite, nous proposons deux modèles alternatifs basés sur la programmation stochastique à deux étapes avec recours, et les résolvons par une approche de décomposition de Benders intégrée à une technique d’approximation moyenne d’échantillon (SAA). Par la suite, nous nous intéressons à la livraison du dernier kilomètre dans un contexte urbain où les décisions de transport dans le deuxième échelon sont caractérisées par des tournées de véhicules. Un problème multi-période stochastique de localisation-routage à deux échelons avec capacité (2E-SM-CLRP) est défini, dans lequel les décisions de localisation concernent les WPs et les DPs. Le modèle est un programme stochastique à deux étapes avec recours en nombre entier. Nous développons un algorithme de décomposition de Benders. Les décisions de localisation et de capacité sont déterminées par la solution du problème maître de Benders. Le sous-problème résultant est un problème multi-dépôt de tournées de véhicule avec des dépôts et véhicules capacitaires qui est résolu par un algorithme de branch-cut-and-price.Enfin, nous étudions le cadre à plusieurs étapes proposé pour le problème stochastique multi-période de design de réseaux de distribution à deux échelons et évaluons sa tractabilité. Pour ceci, nous développons une heuristique à horizon glissant qui permet d’obtenir des bornes de bonne qualité et des solutions de design pour le modèle à plusieurs étapes. / With the high growth of e-commerce and the continuous increase in cities population contrasted with the rising levels of congestion, distribution schemes need to deploy additional echelons to offer more dynamic adjustment to the requirement of the business over time and to cope with all the random factors. In this context, a two-echelon distribution network is nowadays investigated by the practitioners.In this thesis, we first present a global survey on distribution network design problems and point out many critical modeling features, namely the two-echelon structure, the multi-period setting, the uncertainty and solution approaches. The aim, here, is to propose a comprehensive framework for the design of an efficient two-echelon distribution network under multi-period and stochastic settings in which products are directed from warehouse platforms (WPs) to distribution platforms (DPs) before being transported to customers. A temporal hierarchy characterizes the design level dealing with facility-location and capacity decisions over a set of design periods, while the operational level involves transportation decisions on a daily basis.Then, we introduce the comprehensive framework for the two-echelon distribution network design problem under uncertain demand, and time-varying demand and cost, formulated as a multi-stage stochastic program. This work looks at a generic case for the deployment of a retailer's distribution network. Thus, the problem involves, at the strategic level, decisions on the number and location of DPs along the set of design periods as well as decisions on the capacity assignment to calibrate DP throughput capacity. The operational decisions related to transportation are modeled as origin-destination arcs. Subsequently, we propose alternative modeling approaches based on two-stage stochastic programming with recourse, and solve the resulting models using a Benders decomposition approach integrated with a sample average approximation (SAA) technique.Next, we are interested in the last-mile delivery in an urban context where transportation decisions involved in the second echelon are addressed through multi-drop routes. A two-echelon stochastic multi-period capacitated location-routing problem (2E-SM-CLRP) is defined in which facility-location decisions concern both WPs and DPs. We model the problem using a two-stage stochastic program with integer recourse. To solve the 2E-SM-CLRP, we develop a Benders decomposition algorithm. The location and capacity decisions are fixed from the solution of the Benders master problem. The resulting subproblem is a capacitated vehicle-routing problem with capacitated multi-depot (CVRP-CMD) and is solved using a branch-cut-and-price algorithm.Finally, we focus on the multi-stage framework proposed for the stochastic multi-period two-echelon distribution network design problem and evaluate its tractability. A scenario tree is built to handle the set of scenarios representing demand uncertainty. We present a compact formulation and develop a rolling horizon heuristic to produce design solutions for the multi-stage model. It provides good quality bounds in a reasonable computational times.

In the warehouse of a large cosmetics company, a mechanized order picker is restocked from nearby shelving, and the shelving is restocked from bulk storage, forming a three-tier inventory system. We consider such multi-tier inventory systems and determine the storage areas to which to assign items, and the quantities in which to store them, in order to minimize the total cost of picking items and restocking storage locations. With this research, we increase the number of inventory systems for which simple search algorithms find a provably near-optimal solution. The model and method were tested on data from the Avon Products distribution center outside Atlanta; the solution identified by the model reduced picking and restocking costs there by 20%. The sales forecasts of items stored in the warehouse may change, however, and new items will be introduced into the inventory system and others removed. To account for these changes, some warehouses may periodically reassign items to storage areas and recompute their storage quantities. These reassignment activities account for additional costs in the warehouse. The second focus of this research examines these costs over several time periods in a simple multi-tier inventory system. We develop heuristics to determine the storage areas to which to assign items and the quantities in which to store them in each time period, in order to minimize the total cost of picking items, restocking storage locations, and reassigning skus over multiple periods.

Vendor Managed Inventory (VMI) policy has been widely used in various supply chains due to the benefits such as lower inventory levels and costs of retailer, and less frequent stock outs. In this study, the benefits of VMI policy in a manufacturer-retailer setting are analyzed under three different scenarios (Traditional Decision Making, VMI agreement and Centralized Decision Making). A manufacturer that produces a particular product is considered and that product is sold to a retailer operating under known demand forecasts. Under Traditional Decision Making System, each party is responsible for its own costs. Under VMI, manufacturer controls the replenishment decisions of the retailer and solves a Constrained Two-Echelon Lot Sizing Problem with Backordering. Under Centralized Decision Making, manufacturer and retailer act like merged, the problem under consideration is Two-Echelon Single Item Lot Sizing with Backordering. Through an extensive numerical study, three different scenarios&rsquo / results are compared and the conditions beneficial under VMI are identified. Under VMI, a Lagrangean Relaxation algorithm is proposed to reduce solution time. In terms of computational effort, solution times of proposed algorithm and MIP model are compared.

The subject of this thesis is to become familiar with the different parameters describing the lines, and the possibility of modeling data and power models. The thesis also outlined the difference in the mechanical structure of different types of cables. The practical part focuses only on the power cables and measure their basic parameters. Then is created computer model which describes the behavior of cable lines at higher frequencies than are primarily intended. The final section is an experimental network created by the PLC for remote reading of electricity meters, and it measured different transmission properties.

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Purpose: Firm innovation is relevant in the fast paced business world. Recent years, research on board diversity has found that demographic and cognitive diversity have an impact on innovation, however this research is still inconclusive. To contribute to the research this thesis introduces informal hierarchy as a moderating variable to investigate if this can explain the previous contradictory findings.  Theoretical perspective: By using concepts from resource dependence theory, upper echelons theory, and behavioral theory, five hypotheses were formulated and tested.  Method: For board diversity Blau’s index was used, innovation was defined as an index of strategic change and informal hierarchy was measured as the dispersion of rank within the board, through the gini coefficient. 186 Swedish publicly listed limited liability firms were analyzed. Findings: The results provided evidence that neither demographic nor cognitive board diversity impacts innovation and informal hierarchy does not have a moderating role on that relationship. However, the findings suggest a direct relationship between informal hierarchy and innovation. Another finding suggests that board size and informal hierarchy separately has a negative impact on innovation, however when both board size and informal hierarchy is present there is a slightly positive effect on innovation.

Understanding managerial behavior and its underlying motivations is of key interest in times where the role of business in society is generally viewed critically. While CEO influence on strategy making processes is almost undisputed, little attention has explicitly been paid to how CEO values and the characteristics of the top management team (TMT) interact in shaping corporate strategy making. This is surprising if one follows the assumption that top managers who work closely together will by necessity influence each other's actions. Hence, we would expect the CEO-TMT interface to be vital in understanding how leadership influences strategy making. To address this, we propose a model in which the personal values of the CEO have a direct effect on the characteristics of corporate strategy making processes yet where this association is moderated by TMT diversity. We test the model with data from Austria and Germany obtained through a large-scale survey conducted in spring 2015 and a follow-up survey conducted in fall 2015 and find general support for our model. CEO values geared towards self-transcendence (as opposed to selfinterest) seem to be associated with more formal strategy making processes, while values geared towards openness to change (as opposed to conservation) are found to be associated with more flexible and less externally open ones. TMT diversity moderates all of these relationships. Our results add to upper echelon theory as well as to strategy process research and highlight promising avenues for future research.

O foco dessa dissertação está na gestão de estoques em sistemas multicamadas. O modelo de simulação construído considera o desempenho histórico de uma cadeia de distribuição de medicamentos versus a política de gestão proposta. Os objetivos principais do trabalho são: a avaliação quantitativa da política de cálculo de necessidades aplicada na gestão de sistemas multicamadas, a verificação da importância da cooperação entre os elos da cadeia de distribuição para gestão do fluxo de materiais e o estudo das curvas que representam o dilema ‘nível de serviço’ versus ‘custo total da cadeia’. O modelo considera o fluxo de materiais a partir do estoque em processo do laboratório até a venda para as farmácias, que pode ser aproximada pela demanda dos medicamentos visto que os estoques das farmácias são relativamente pequenos e constantes ao longo do tempo. A modelagem de custos leva em conta o custo de estoque do laboratório e dos distribuidores, o custo de pedido dos distribuidores, o custo de transporte, o custo de entrega com atraso do laboratório e o custo de venda perdida dos distribuidores. Especificamente, são considerados cenários com e sem o compartilhamento de informações entre as empresas da cadeia. Consideram-se também cenários com e sem sazonalidade na demanda. Inicialmente, cada cenário simulado é preparado com a definição do ‘período transitório da simulação’, ‘horizonte de simulação’ e ‘número de réplicas’ necessárias. Depois disso, é feito o delineamento de experimentos para identificar quais variáveis de decisão têm efeito significativo sobre o custo total da cadeia. Finalmente, é feita uma busca da parametrização de cada um dos cenários que apresente o melhor custo total da cadeia. Os resultados da simulação mostraram que as práticas atualmente empregadas na gestão dos estoques das empresas podem ter seu desempenho melhorado com a utilização da política simulada na pesquisa. Os cenários nos quais se considerou o compartilhamento de informações tiveram desempenhos semelhantes aos sem esse compartilhamento. Dessa forma, para a política simulada, conclui-se que o valor do compartilhamento de informações foi relativamente pequeno. Nas simulações pode-se verificar a melhoria simultânea do nível de serviço e do nível de estoques da cadeia. Isso mostra que a política simulada mudou o dilema (trade-off) que interliga antagonicamente essas duas características de desempenho do sistema. / This dissertation focuses on the inventory management for multi-echelon systems. The simulation model proposes a new inventory management policy and compares it to the historical performance of a medicine supply chain. The main objectives of this research are: the quantitative analysis of the method used for the calculation of material requirements in multi-echelon systems; the verification of the importance of the cooperation between the components of the supply chain to the material flow management; and the analysis of the curves which represent the trade-off between ‘service level’ and ‘total cost’. The model takes into account the material flow from the laboratory’s ‘work in process’ up to the sales to the drugstores, which can be approximated by the demand of the final consumer, since the inventory kept by drugstores is relatively small and constant in time. The costs are calculated considering: the laboratory’s and distributors’ inventory costs, the cost of orders from the distributors, the transportation cost, the laboratory’s cost of late delivery and the distributors’ cost of lost sales. Scenarios with and without the sharing of information between the components of the supply chain were both considered. The same is true for scenarios with and without seasonality in the demand. Initially, each scenario was prepared with the definition of the ‘warm-up’ period, the simulation horizon and the amount of required replications. Secondly, the design of experiments (DOE) was done in order to determine which decision variables have influence on the supply chain total cost. Finally, each scenario was tested with many different parameters in order to find the lowest cost for the supply chain. The simulation results have showed that the procedures currently applied for the inventory management can have their performance improved by the use of the policy proposed in this research. The results for the scenarios with the sharing of information were similar to the ones for the scenarios without the sharing. For that reason, we can conclude that, for the proposed inventory management policy, the value of the sharing of information through the supply chain was relatively small. In the simulations, both the ‘service level’ and the ‘total cost’ have improved. In this manner, it can be said that the new policy has improved this trade-off.

Nesta tese propõe-se um método heurístico para o problema de Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) considerando vários aspectos de relevância prática, tais como: fornecedores e matérias-primas, localização e operação de instalações, atribuição de Centros de Distribuição (CD), e grande número de clientes e produtos. Uma eficiente abordagem heurística de duas fases é proposta para a obtenção de soluções viáveis para os problemas, que inicialmente é modelado como um Programa Linear Inteiro Misto (PLIM) de grande escala. Na fase de construção, uma estratégia de Linear Programming Rounding é aplicada para se obter os valores iniciais para as variáveis de localização inteira do modelo. Simultaneamente, um método Multi-start foi desenvolvido para gerar soluções iniciais diversificadas para cada nova iteração da heurística de Rounding. Na segunda fase, dois procedimentos de Busca Local foram desenvolvidos no sentido de melhorar a solução fornecida pelo método de Rounding. Implementamos duas diferentes abordagens de Busca Local: remoção-inserção e troca. Uma técnica de Busca Tabu para orientar o procedimento de Busca Local para explorar os diferentes espaços de soluções foi desenvolvida. As formulações e algoritmos foram implementados na linguagem C++ utilizando ferramentas de otimização da COIN-OR. O método de solução foi experimentado em instâncias geradas aleatoriamente, com tamanhos diferentes em termos do número de parâmetros, tais como o número de produtos, zonas de clientes, CDs e fábricas considerando um sistema logístico de quatro níveis. As implementações computacionais mostram que o método de solução proposto obteve resultados satisfatórios quando comparados com a literatura. Para validar este método heurístico também foi usado em um caso realista, com base em dados de uma empresa de borracha que está reestruturando sua cadeia de suprimentos devido ao projeto de uma nova uma nova fábrica e produção de novos produtos. A abordagem heurística proposta revelou-se adequada para aplicação prática em um caso real de uma indústria multicommodity em um contexto determinístico. / In this thesis we propose a heuristic method for the Supply Chain Network Design (SCND) problem considering several aspects of practical relevance: suppliers and raw materials, location and operation facilities, distribution center (DC) assignments, and large numbers of customers and products. An efficient two-phase heuristic approach is proposed for obtaining feasible solutions to the problems, which is initially modeled as a large-scale Mixed Integer Linear Program (MILP). In the construction phase, a linear programming rounding strategy is applied to obtain initial values for the integer location variables in the model. Simultaneously, a Multi-start method was developed to generate diversified initial solutions from each new iteration in the rounding heuristic. In the second phase, two Local Search procedures were developed towards to improve the solution provided by the rounding method. We implemented two different Local Search approaches: removal-insertion and exchange. A Tabu Search technique was developed to guide the Local Search procedure to explore the different spaces of solutions. The formulations and algorithms were implemented in C++ code language using the optimization engine COIN-OR. The solution method was experimented in randomly generated instances, with different sizes in terms of the number of parameters, such as number of products, customer zones, DCs, and factories considering a four-echelon logistic system. The computational implementations show that the solution method proposed obtained satisfactory results when compared to the literature review. To validate this heuristic method was also used in a realistic case, based on data from a rubber company that is restructuring its supply chain due to the overture of a new factory, producing new products. The proposed heuristic approach proved appropriate to practical application in a realistic case of a multi commodity industry in a deterministic context.

Nesta tese propõe-se um método heurístico para o problema de Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) considerando vários aspectos de relevância prática, tais como: fornecedores e matérias-primas, localização e operação de instalações, atribuição de Centros de Distribuição (CD), e grande número de clientes e produtos. Uma eficiente abordagem heurística de duas fases é proposta para a obtenção de soluções viáveis para os problemas, que inicialmente é modelado como um Programa Linear Inteiro Misto (PLIM) de grande escala. Na fase de construção, uma estratégia de Linear Programming Rounding é aplicada para se obter os valores iniciais para as variáveis de localização inteira do modelo. Simultaneamente, um método Multi-start foi desenvolvido para gerar soluções iniciais diversificadas para cada nova iteração da heurística de Rounding. Na segunda fase, dois procedimentos de Busca Local foram desenvolvidos no sentido de melhorar a solução fornecida pelo método de Rounding. Implementamos duas diferentes abordagens de Busca Local: remoção-inserção e troca. Uma técnica de Busca Tabu para orientar o procedimento de Busca Local para explorar os diferentes espaços de soluções foi desenvolvida. As formulações e algoritmos foram implementados na linguagem C++ utilizando ferramentas de otimização da COIN-OR. O método de solução foi experimentado em instâncias geradas aleatoriamente, com tamanhos diferentes em termos do número de parâmetros, tais como o número de produtos, zonas de clientes, CDs e fábricas considerando um sistema logístico de quatro níveis. As implementações computacionais mostram que o método de solução proposto obteve resultados satisfatórios quando comparados com a literatura. Para validar este método heurístico também foi usado em um caso realista, com base em dados de uma empresa de borracha que está reestruturando sua cadeia de suprimentos devido ao projeto de uma nova uma nova fábrica e produção de novos produtos. A abordagem heurística proposta revelou-se adequada para aplicação prática em um caso real de uma indústria multicommodity em um contexto determinístico. / In this thesis we propose a heuristic method for the Supply Chain Network Design (SCND) problem considering several aspects of practical relevance: suppliers and raw materials, location and operation facilities, distribution center (DC) assignments, and large numbers of customers and products. An efficient two-phase heuristic approach is proposed for obtaining feasible solutions to the problems, which is initially modeled as a large-scale Mixed Integer Linear Program (MILP). In the construction phase, a linear programming rounding strategy is applied to obtain initial values for the integer location variables in the model. Simultaneously, a Multi-start method was developed to generate diversified initial solutions from each new iteration in the rounding heuristic. In the second phase, two Local Search procedures were developed towards to improve the solution provided by the rounding method. We implemented two different Local Search approaches: removal-insertion and exchange. A Tabu Search technique was developed to guide the Local Search procedure to explore the different spaces of solutions. The formulations and algorithms were implemented in C++ code language using the optimization engine COIN-OR. The solution method was experimented in randomly generated instances, with different sizes in terms of the number of parameters, such as number of products, customer zones, DCs, and factories considering a four-echelon logistic system. The computational implementations show that the solution method proposed obtained satisfactory results when compared to the literature review. To validate this heuristic method was also used in a realistic case, based on data from a rubber company that is restructuring its supply chain due to the overture of a new factory, producing new products. The proposed heuristic approach proved appropriate to practical application in a realistic case of a multi commodity industry in a deterministic context.