Nous considérons des problèmes de gestion des stocks multi-échelon à temps périodique avec des demandes non stationnaires. Ces hypothèses sur la demande apparaissent notamment lorsque des prévisions sur la demande sont utilisées dynamiquement (de nouvelles prévisions sont fournies à chaque période). La structure des coûts comprend des coûts fixes et variables d’approvisionnement, des coûts de stockage et des coûts de mise en attente des demandes. Le délai d’approvisionnement est supposé constant. Le problème consistant à déterminer la politique optimale qui minimise les coûts sur un horizon fini peut être formulé grâce à un programme dynamique. Dans le cadre déterministe, les problèmes auxquels nous nous intéressons sont le plus souvent NP-difficiles, ce qui fait rapidement exploser l’espace d’état. Il devient alors nécessaire de recourir à des heuristiques. Nous nous orientons vers la recherche d'algorithmes d'approximation combinatoires pour le problème One Warehouse Multi Retailers et plus généralement pour des systèmes de distribution divergents. Nous nous intéresserons dans un premier temps à des systèmes de distribution à deux étages avec un entrepôt central et des entrepôts secondaires qui voient la demande finale. Dans un deuxième temps, des structures logistiques plus complexes pourront être considérées. L’objectif sera de proposer des heuristiques originales, basées sur des techniques de répartition des coûts, de les comparer numériquement à la politique optimale sur de petites instances et, si possible, d’établir des garanties de performance. / Inventory management has always been a major component of the field of operations research and numerous models derived from the industry aroused the interest of both the researchers and the practitioners. Within this framework, our work focuses on several classical inventory problems, for which no tractable method is known to compute an optimal solution. Specifically, we study deterministic models, in which the demands of the customers are known in advance, and we propose approximation techniques for each of the corresponding problems that build feasible approximate solutions while remaining computationally tractable. We first consider continuous-time models with a single facility when demand and holding costs are time-dependent. We present a simple technique that balances the different costs incurred by the system and we use this concept to build approximation methods for a large class of such problems. The second part of our work focuses on a discrete time model, in which a central warehouse supplies several retailers facing the final customers demands. This problem is known to be NP-hard, thus finding an optimal solution in polynomial time is unrealistic unless P=NP. We introduce a new decomposition of the system into simple subproblems and a method to recombine the solutions to these subproblems into a feasible solution to the original problem. The resulting algorithm has a constant performance guarantee and can be extended to several generalizations of the system, including more general cost structures and problems with backlogging or lost-sales.

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.

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.

The supply function has an important role to support the business to create a customer value. Two important parts of this process is to have the warehouses and production sites in the right location and to have the right items stocked at the right level.   This thesis is concerned with those two parts of the supply chain management. Three different areas of inventory control are dealt with. In the first part we consider the classical dynamic lot size problem without backlogging. The second part deals with estimation of holding and shortage costs in two-level distribution inventory systems. In the third part of the thesis we consider the localisation problem in a multi-level supply network system where items are consolidated at a warehouse and distributed to customers on routes.   Within the area of inventory control we have evaluated a method earlier suggested by Axsäter (1988), the method is evaluated using a set of test problems and compared other heuristic methods, including the well-known Silver-Meal’s method (Silver and Meal, 1973).  The result shows that the method suggested by Axsäter does perform better than the other methods. In the latest contribution we point to the important differences between Least Period Cost and Silver-Meal when several periods have zero demand. In the area of inventory control we have also studied a two-echelon inventory system where we present methods for estimating the shortage- and stockholding costs in such inventory systems.   The second part subject of the thesis concerns supply network optimization. We present a MIP formulation of the problem and evaluate in detail the approximation of the distribution cost when customers are delivered on multi-stop routes. An improved method for estimating the distribution is presented.   Besides this introductory overview five research papers are included in the thesis. The first and the last paper consider evaluation of dynamic lot sizing heuristics. The second and third paper deals with cost evaluation of a stochastic two-echelon inventory system and the forth paper with evaluation of methods for estimating distribution costs in a supply network.

Les activités de transport et de gestion des stocks ont un impact important les unes sur les autres. Assurer un niveau de stock idéal peut demander des livraisons fréquentes, ce qui entraîne des coûts logistiques élevés. Pour optimiser les compromis entre les coûts de stock et de transport, des systèmes VMI (Vendor Managed Inventory) ont été développés pour gérer ensemble les opérations de stock et de transport. Pour un ensemble de clients ayant des demandes sur un horizon de temps, le problème de détermination des tournées et des quantités à livrer avec un coût minimum de gestion de stock et de transport est connu sous le nom de Inventory Routing Problem (IRP). Les systèmes à deux échelons ont également été étudiés pour améliorer le flux de véhicules dans les zones urbaines. étant donné que des nouvelles politiques de gestion sont apparues, dans le but de limiter le trafic des gros véhicules et leur vitesse dans les centres urbains, des Centres de Distribution (DC) sont mis en place pour coordonner les flux de marchandises à l'intérieur et à l'extérieur des zones urbaines. Les produits sont donc livrés aux clients par les fournisseurs via les DC.Nous proposons de combiner un système à deux échelons avec le IRP. Nous introduisons un Operational Two-Echelon Inventory Routing Problem (O-2E-IRP), ce qui est une nouvelle extension du IRP à notre connaissance. Dans le O-2E-IRP proposé, les clients doivent être servis par un fournisseur strictement via des DC et les tournées doivent être définis dans les deux échelons sur un horizon de temps donné. Trois politiques de réapprovisionnement et de configurations de routage différentes sont modélisées pour ce problème. Nous développons deux formulations mathématiques, ainsi qu'un algorithme Branch-and-Cut (B&C) combiné à une matheuristique pour résoudre le problème. De plus, nous analysons plusieurs inégalités valides disponibles pour le IRP et nous introduisons de nouvelles inégalités valides inhérentes au IRP à deux échelons. Des expériences de calcul approfondies ont été effectuées sur un ensemble d'instances générées de manière aléatoire. Les résultats obtenus montrent que les performances des méthodes sont liées à la politique de stock et à la configuration de routage.Dans le contexte d'un IRP à deux échelons, deux décisions tactiques importantes doivent être prises en plus des décisions de livraison de routage et de quantité de livraison: à partir de quel DC sera fourni chaque client et en utilisant quels véhicules ? Répondre à ces questions est extrêmement difficile car cela implique de pouvoir minimiser les coûts opérationnels d'un système de livraison VMI à deux échelons à long-terme et avec des demandes incertaines. Pour faire face à cela, nous présentons le Tactical Two-Echelon Inventory Routing Problem (T-2E-IRP) qui optimise les décisions en fonction d'un horizon à long-terme et en tenant compte des demandes stochastiques. Trois politiques de gestion des stocks sont modélisées et appliquées à un ou aux deux échelons. Nous développons une approche de simulation pour résoudre le T-2E-IRP sur un horizon de temps à long-terme. Nous proposons quatre formulations et deux algorithmes B&C pour définir l'affectation des clients et des véhicules aux DC en fonction d'un horizon de temps court. Ensuite, nous évaluons ces décisions d'affectation via un outil de simulation qui résout un sous-problème du T-2E-IRP, qui consiste en les décisions de livraisons du fournisseur aux DC et des DC aux clients, sur un horizon glissant. De nombreuses expériences sont effectuées pour un ensemble d'instances générées aléatoirement. L'impact de plusieurs paramètres utilisés pour déterminer l'affectation des clients et des véhicules aux DC sur le coût total est analysé. Basé sur des expériences, nous définissons la combinaison de paramètres qui fournit généralement les meilleurs résultats sur les instances générées. / Transport and inventory management activities have a great impact on each other. Ensuring an ideal inventory level can require frequent deliveries, leading to high logistics costs. To optimize the trade-offs between inventory and transportation costs, VMI (Vendor Managed Inventory) systems have been developed to manage inventory and transportation operations together. Given a set of customers with demands over a time horizon, the problem of determining routes and delivery quantities at a minimum inventory holding and transportation costs is known as Inventory Routing Problem (IRP). Two-echelon systems have also been studied to improve the freight vehicle flow inside urban areas. As new management policies have emerged, with the goal of limiting the traffic of large vehicles and their speed in urban centers, Distribution Centers (DC) are introduced to coordinate freight flows inside and outside the urban areas. Products are then delivered from the suppliers to the customers through the DC.We propose to combine a two-echelon system with the IRP. We introduce an Operational Two-Echelon Inventory Routing Problem (O-2E-IRP), which is a new extension of the IRP to the best of our knowledge. On the proposed O-2E-IRP, the customers must be served by a supplier strictly through DC and routes must be defined in both echelons over a given time horizon. Three different replenishment policies and routing configurations are modeled for this problem. We develop two mathematical formulations, and a Branch-and-Cut (B&C) algorithm combined with a matheuristic to solve the problem. In addition, we analyze several valid inequalities available for IRP, and we introduce new ones inherent to the IRP within two echelons. Extensive computational experiments have been carried out on a set of randomly generated instances. The obtained results show that the performance of the methods is related to the inventory policy and routing configuration.In the context of a two-echelon IRP, two important tactical decisions have to be taken in addition to route and quantity delivery decisions: from which DC will be supplied each customer and using which vehicles? Answering these questions is extremely difficult as it implies being able to minimize operational costs for a two-echelon VMI delivery system on long-term and with uncertain demands. In order to deal with this, we introduce the Tactical Two-Echelon Inventory Routing Problem (T-2E-IRP) that optimizes the decisions based on a long-term horizon and considering stochastic demands. Three inventory management policies are modeled and applied at one or both echelons. We develop a simulation approach to solve the T-2E-IRP on a long-term time horizon. We propose four formulations and two B&C algorithms to define the assignment of customers and vehicles to the DC based on a short time horizon. Then, we evaluate these assignment decisions through a simulation tool that solves a subproblem of the T-2E-IRP, which consists of the decisions of deliveries from the supplier to the DC and from the DC to the customers, on a rolling-horizon framework. Extensive computational experiments are performed for a set of randomly generated instances. The impact of several parameters used to determine the assignment of customers and vehicles to DC on the total cost is analyzed. Based on the experiments, we define the combination of parameters that generally provides the best results on the generated instances.

Purpose – To find out what factors hinder and promote SMEs to practice sustainable business. Methodology – Qualitative case study based on interviews and archival data. Findings – This research resulted in five different propositions. 1. Corporate reputation plays a role in contributing to  SMEs’ sustainable practices. 2. The scarce resources of SMEs induce difficulties to maintain a balance between short-term financial goals and long-term sustainability goals, which hinders SMEs to undertake sustainable practices. 3. The scarce resources of SMEs induce internal misalignments in expectations between different stakeholders, which hinders SMEs to undertake sustainable practices. 4. Affiliations and social networks of top managers play a role in contributing to their SMEs’ sustainable practices. played a vital role in promoting the sustainability practices of their SMEs. 5. Less diversity in the top management team hinders SMEs’ sustainable practices. Contributions - This thesis enhances understanding of the factors influencing the implementation of sustainable practices in SMEs from a manager's perspective, filling a knowledge gap in the financial sector. It also provides insights into the complex relationship between subsidiaries and headquarters, highlighting the dynamic balance between sustainability, financial goals, and directives from the headquarters.

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Background: Prior literature on diversity within BODs and TMTs is predominantly situated within thecontext of conventional organizations. However, sports clubs differ somewhat fromconventional organizations due to the inclusion of an additional performance metric toconsider, sports performance, which stands as their foremost priority. As sports clubsoperate under a heightened-paced landscape with far more external pressure, the necessityto extend governance research into this rather new area of investigation is of interest. Purpose: The purpose of the thesis is to investigate the impact of BOD and TMT diversity on sportsclubs’ sports and financial performance and how media influence this relationship. Method: This thesis employs a deductive approach, utilizing a quantitative method, to investigatethe research objectives. The analysis is based on 144 observations from 24 distinct Swedishsports clubs. Depending on the performance metrics being measured, the data is examinedusing either multiple linear regression or ordinal regression. Conclusion: The study supports three of its eight hypotheses, namely that BOD diversity has a positiverelationship with sports performance and that media moderate the relationship betweenTMT diversity, partially BOD diversity and financial performance.

This thesis presents a comprehensive investigation into the performance and generalizability of optimization approaches for the single-echelon (r, Q) inventory management policy under stochastic demand, specifically focusing on demand characterized by a Poisson distribution. The research integrates both classical optimization techniques and advanced metaheuristic methods, with a particular emphasis on Genetic Programming (GP), to assess the effectiveness of various heuristics. The study systematically compares the performance of these approaches in terms of both accuracy and computational efficiency using two well-known datasets. To rigorously evaluate the generalizability of the heuristics, an extensive random dataset of 10,000 instances, drawn from a vast population of approximately 24 billion instances, was generated and employed in this study. Our findings reveal that the exact solution provided by the Federgruen-Zheng Algorithm consistently outperforms hybrid heuristics in terms of computational efficiency, confirming its reliability in smaller datasets where precise solutions are critical. Additionally, the extended Cooperative Coevolutionary Genetic Programming (eCCGP) heuristic proposed by Lopes et al. emerges as the most efficient in terms of runtime, achieving a remarkable balance between speed and accuracy, with an optimality error gap of only 1%. This performance makes the eCCGP heuristic particularly suitable for real-time inventory management systems, especially in scenarios involving large datasets where computational speed is paramount. The implications of this study are significant for both theoretical research and practical applications, suggesting that while exact solution, i.e., the Federgruen-Zheng Algorithm is ideal for smaller datasets, the eCCGP heuristic provides a scalable and efficient alternative for larger, more complex datasets without substantial sacrifices in accuracy. These insights contribute to the ongoing development of more effective inventory management strategies in environments characterized by stochastic demand. / Thesis / Master of Science (MSc)