Nesse trabalho apresentamos a modelagem matemática do Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) de uma empresa responsável pela produção e distribuição de commodities. O investimento em uma nova fábrica exige que a empresa tenha seu projeto logístico readequado. O desenvolvimento das formulações matemáticas é baseado no trabalho de Jayaraman e Pirkul (2001). Foram realizadas 3 (três) formulações matemáticas de diferentes abordagens para solução do projeto logístico. As implementações computacionais foram realizadas no CPLEX© Optimization Studio Academic Research versão 12.2. As experiências computacionais foram desenvolvidas através de cenários que buscaram representar problemas de dimensões reais. Ainda na etapa de experimentação foram realizadas análises de sensibilidade dos modelos. Um estudo para identificar as demandas de mercado e os custos de transporte foi realizado, sendo assim, foi possível aplicar os modelos no estudo de caso a partir de dados reais de demanda e custos. Para execução das instâncias reais foram selecionadas 2 (duas) abordagens distintas: Single-source e Arcbased. Diferentes market shares foram definidos para construção de novos cenários e instâncias reais foram executadas dentro de limites computacionais de tempo satisfatórios. Os resultados encontrados para cada cenário foram comparados e analisados em relação à resolução do problema proposto. A dissertação contribui para a área de modelagem da cadeia de suprimentos fornecendo modelos que apresentaram resultados satisfatórios para a tomada de decisão nessa fase do projeto logístico da indústria tema dessa pesquisa. / We present a mathematical modeling of the Supply Chain Network Design (SCND) for a company responsible for producing and distributing commodities. Investment in a new plant requires that the company has reconfigured its logistics project. The development of mathematical formulations is based on the work of Jayaraman and Pirkul (2001). Were performed three (3) mathematical formulations for different approaches to solving the logistics project. Computational implementations were done in CPLEX© Optimization Academic Research Studio version 12.2. Computational experiments were developed through scenarios that sought to represent problems of the real dimensions. Still in the experimentation fase were performed sensitivity analysis of models. A study to identify market demands and transportation costs was made, so the models could be applied in the case study data from actual demand and costs. For carrying out the actual instances were selected 2 (two) different approaches: Single-source-based and Arc. Different market shares were set to build new scenarios and actual instances have been implemented within limits satisfactory computational time. The results for each scenario were compared and analyzed for solving the proposed problem. The thesis contributes to modeling area of supply chain models that provide satisfactory results for decision making in this phase of the project's logistics industry theme of this research.

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.

Nesse trabalho apresentamos a modelagem matemática do Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) de uma empresa responsável pela produção e distribuição de commodities. O investimento em uma nova fábrica exige que a empresa tenha seu projeto logístico readequado. O desenvolvimento das formulações matemáticas é baseado no trabalho de Jayaraman e Pirkul (2001). Foram realizadas 3 (três) formulações matemáticas de diferentes abordagens para solução do projeto logístico. As implementações computacionais foram realizadas no CPLEX© Optimization Studio Academic Research versão 12.2. As experiências computacionais foram desenvolvidas através de cenários que buscaram representar problemas de dimensões reais. Ainda na etapa de experimentação foram realizadas análises de sensibilidade dos modelos. Um estudo para identificar as demandas de mercado e os custos de transporte foi realizado, sendo assim, foi possível aplicar os modelos no estudo de caso a partir de dados reais de demanda e custos. Para execução das instâncias reais foram selecionadas 2 (duas) abordagens distintas: Single-source e Arcbased. Diferentes market shares foram definidos para construção de novos cenários e instâncias reais foram executadas dentro de limites computacionais de tempo satisfatórios. Os resultados encontrados para cada cenário foram comparados e analisados em relação à resolução do problema proposto. A dissertação contribui para a área de modelagem da cadeia de suprimentos fornecendo modelos que apresentaram resultados satisfatórios para a tomada de decisão nessa fase do projeto logístico da indústria tema dessa pesquisa. / We present a mathematical modeling of the Supply Chain Network Design (SCND) for a company responsible for producing and distributing commodities. Investment in a new plant requires that the company has reconfigured its logistics project. The development of mathematical formulations is based on the work of Jayaraman and Pirkul (2001). Were performed three (3) mathematical formulations for different approaches to solving the logistics project. Computational implementations were done in CPLEX© Optimization Academic Research Studio version 12.2. Computational experiments were developed through scenarios that sought to represent problems of the real dimensions. Still in the experimentation fase were performed sensitivity analysis of models. A study to identify market demands and transportation costs was made, so the models could be applied in the case study data from actual demand and costs. For carrying out the actual instances were selected 2 (two) different approaches: Single-source-based and Arc. Different market shares were set to build new scenarios and actual instances have been implemented within limits satisfactory computational time. The results for each scenario were compared and analyzed for solving the proposed problem. The thesis contributes to modeling area of supply chain models that provide satisfactory results for decision making in this phase of the project's logistics industry theme of this research.

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.

Nesse trabalho apresentamos a modelagem matemática do Projeto de Rede da Cadeia de Suprimentos (Supply Chain Network Design) de uma empresa responsável pela produção e distribuição de commodities. O investimento em uma nova fábrica exige que a empresa tenha seu projeto logístico readequado. O desenvolvimento das formulações matemáticas é baseado no trabalho de Jayaraman e Pirkul (2001). Foram realizadas 3 (três) formulações matemáticas de diferentes abordagens para solução do projeto logístico. As implementações computacionais foram realizadas no CPLEX© Optimization Studio Academic Research versão 12.2. As experiências computacionais foram desenvolvidas através de cenários que buscaram representar problemas de dimensões reais. Ainda na etapa de experimentação foram realizadas análises de sensibilidade dos modelos. Um estudo para identificar as demandas de mercado e os custos de transporte foi realizado, sendo assim, foi possível aplicar os modelos no estudo de caso a partir de dados reais de demanda e custos. Para execução das instâncias reais foram selecionadas 2 (duas) abordagens distintas: Single-source e Arcbased. Diferentes market shares foram definidos para construção de novos cenários e instâncias reais foram executadas dentro de limites computacionais de tempo satisfatórios. Os resultados encontrados para cada cenário foram comparados e analisados em relação à resolução do problema proposto. A dissertação contribui para a área de modelagem da cadeia de suprimentos fornecendo modelos que apresentaram resultados satisfatórios para a tomada de decisão nessa fase do projeto logístico da indústria tema dessa pesquisa. / We present a mathematical modeling of the Supply Chain Network Design (SCND) for a company responsible for producing and distributing commodities. Investment in a new plant requires that the company has reconfigured its logistics project. The development of mathematical formulations is based on the work of Jayaraman and Pirkul (2001). Were performed three (3) mathematical formulations for different approaches to solving the logistics project. Computational implementations were done in CPLEX© Optimization Academic Research Studio version 12.2. Computational experiments were developed through scenarios that sought to represent problems of the real dimensions. Still in the experimentation fase were performed sensitivity analysis of models. A study to identify market demands and transportation costs was made, so the models could be applied in the case study data from actual demand and costs. For carrying out the actual instances were selected 2 (two) different approaches: Single-source-based and Arc. Different market shares were set to build new scenarios and actual instances have been implemented within limits satisfactory computational time. The results for each scenario were compared and analyzed for solving the proposed problem. The thesis contributes to modeling area of supply chain models that provide satisfactory results for decision making in this phase of the project's logistics industry theme of this research.

D. Tech. (Logistics management, Faculty of Management Science), Vaal University of Technology / Nowadays, the business environment is characterised by faster technological development, customer satisfaction, shorter product life cycles, and more intense global competition. This new competitive landscape has forced firms to acquire new ways to achieve competitive advantage actively since a firm's competitive advantage is now dependent on operating efficiency and productivity across functional areas of the firm. The most successful manufacturers seem to be those that have carefully linked their internal processes to external suppliers and customers in unique supply chains. The manufacturing sector represents 15 per cent of gross domestic product (GDP) of the South African commercial industry. Competitive challenges in the modern business environment have resulted in the need for firms to collaborate their business processes strategically across other business units within the supply chain. Supply chain network theory, dynamic capabilities theory, and the resource-based view theory are discussed to better understand the importance of firms' supply chain capabilities, supply chain agility, and firm performance. The primary objective of this research study was to investigate the association between supply chain capabilities (supply chain network design, supply chain information competency, and supply chain integration) and supply chain agility on firm performance in the manufacturing sector of the Gauteng province in South Africa. It also aimed to ascertain the kind of relationships between supply chain network with supply chain agility, supply chain network with firm performance, supply chain information competency with supply chain agility, supply chain integration with supply chain agility, supply chain integration with firm performance, and finally supply chain agility with firm performance. Structured questionnaires were distributed to various manufacturing firms in the Gauteng province. The data were collected from manufacturing firm managers and owners. SPSS 25.0 was used to analyse the data, and AMOS 25.0 used to perform the confirmatory factor analysis (CFA) and path analysis. The structural equation modelling (SEM) was used to assess the proposed model fit and to test the statistically significant relationship between the various hypotheses. The research study results revealed that supply chain technologies and supply chain vi agility positively influence firm manufacturing performance. This study contributes new knowledge to the existing literature by providing a research framework that can enhance manufacturing firms' performance and also offer practical recommendations based on the research findings for manufacturing firms and future research. Furthermore, as one of the first studies to address the association between supply chain capabilities and supply chain agility on firm performance in the Gauteng province, this study generates new insights and information, as well as outlines the strategic reasons for manufacturing firms' managers and owners to improve on their organisational relationships. Hence, the study found that firms have realised significant supply chain coordination through supply chain capabilities and supply chain agility and that firms have been able to attain strategic goals, reduce risks and improve internal and external coordination of operational processes. Keywords: supply chain network design; supply chain information competency; supply chain integration; supply chain agility; firm performance.

The world is changing, what has been known to work has been put to the test when both the geopolitical and the environmental climate are changing. War, a pandemic, material shortage, financial difficulties and an overall dis- tressed global transportation sector have shown that the ever-more important topic of resilience is crucial to stay relevant in today’s competitive markets. Companies are therefore switching focus towards ensuring sufficient supply chain resilience capabilities to handle these ever-changing situations on the global market.  In this thesis, we focus on how Volvo SML is working with resilience today, and how graph theory and optimisation can be useful tools when analysing a supply chain’s resilience. We made a qualitative analysis by conducting inter- views with employees and comparing our findings with capabilities related to resilience. In addition, we conducted a quantitative analysis by constructing a simulation of the supply chain, comparing two topology metrics and two op- timisation metrics, to analyse the robustness of the aftermarket supply chain.  We analysed the data and summarised the insights gathered from the inter- views using a resilience capability framework. Volvo SML proved to be agile and reactive when dealing with disruptions but is missing some key capabil- ities during the pre-and post-disruption phases. Some areas of improvement we identified were: robustness, collaboration and redundancy. We proved that the simulation is useful when evaluating the robustness of a supply chain, and we showed that a more flexible way of working would improve the overall robustness of Volvo SML’s aftermarket supply chain.

No description available.

This master thesis investigates the integration of sustainability and resilience principles into the design of a distribution supply chain network for copper mining, using a case study at Copperstone Resources AB. The aim is to demonstrate how these considerations can be effectively implemented in the copper mining industry, an area where such integration is largely unexplored. Using a case study approach, an optimization model and sensitivity analysis were developed, resulting in four alternative supply chain network designs: two proposed by the company and two generated by the optimization model. Through multi-criteria decision analysis methods, including the analytical hierarchy process and weighted sum method, the alternatives were assessed with input from Copperstone Resources AB. The findings indicate potential cost savings ranging from 200 to 550 MSEK across the four alternatives over 10 years. The preferred option identified by the analysis involves intermodal transport utilizing electric trucks, railways, and ships to transport copper concentrate to Skelleftehamn and iron concentrate to Amsterdam, Rotterdam, and Antwerp. This alternative is deemed the most efficient, environmentally friendly, and resilient, making it the recommended distribution supply chain network design. It is projected to emit between 25 872 and 81 545 tonnes of CO2 over 10 years, with an estimated investment and operating expense of approximately 2.57 BSEK over the same period. This research contributes to the scientific understanding of integrating sustainability and resilience in supply chain network design, particularly in the copper mining industry. The thesis provides insights for practitioners seeking to optimize their distribution networks while considering environmental and resilience factors.

Cloud computing is a technology that has gained increasing attention because of its considerable benefits, which include reduced costs, reduced complexity and increased flexibility. To obtain these benefits, cloud computing utilizes existing technologies, such as grid computing, virtualization and web services, for online delivery of scalable information technology (IT) services, frequently on the basis of a pay-per-use pricing model. In 2008, the Gartner Group predicted that cloud computing would reach the mainstream within two to five years. However, in their latest hype cycle for emerging technologies, they stated that cloud computing had not yet reached the plateau of productivity but rather was still in the trough of disillusionment. The reason for this situation may be that cloud computing continues to face skepticism because of various concerns regarding, e.g., data privacy and security. In particular, (enterprise) customers transfer (sensitive) data to cloud computing providers, and the end-user rents the right to use cloud computing services via a web browser with minimal need to interact or even without the necessity of interacting directly with a sales assistant. These two aspects result in a strong unilateral dependency and require a high degree of trust in the provider. Additionally, publicity regarding the PRISM program has brought these aspects to the forefront of public interest. Consequently, specific requirements regarding, e.g., security, privacy, accountability, and auditability, must be met to fulfill the expectations of business partners and to build long-term business relationships. Thus, overcoming information asymmetry, enhancing transparency and eradicating behavioral uncertainty is of high importance to build trust between cloud computing providers and their (prospective) customers. Therefore, although most research to date has focused on technical aspects and aimed to improve the actual security of cloud computing services, there is also an urgent need to understand the factors that affect the adoption of cloud computing services from the points of view of both private users and companies. If cloud computing is to reach its full potential, a clear understanding of the factors that influence its adoption is mandatory to improve both present and future cloud computing services. Motivated by these considerations, the aim of this doctoral thesis is to explore, describe, analyze and explain the factors that influence the adoption of cloud computing using various qualitative and quantitative research methods, i.e., by employing a mixed-methods analysis. As a first step, a serious game is conducted to explore various factors that influence the adoption of cloud computing services. Based on these initial findings, the factors explored during the serious game and some additional factors are described and analyzed in detail. These factors include the cloud computing market, costs, trust, affectedness, shadow IT, and sustainability. Furthermore, the factor of information asymmetry, especially regarding bridging the information asymmetry with various information presentation methods, is explained. Following these findings, a research agenda, which contains a recommended research design and lists the theories that are relevant in the context of the adoption of cloud computing, is proposed. Subsequently, a synthesis of the research findings in terms of their implications for practice and research, including limitations, are discussed.