Multiobjective optimization as a decision aid for managing build-to-order supply chains

This paper provides an overview of multiobjective optimization (MOO) as a decision aid in build-to-order supply chains (BTO-SC). The main features of BTO-SCs are discussed along with capabilities of MOO to enhance decision making at different points along the chain. Key decision points across a typical BTO-SC are identified and potential applications of MOO are discussed. A sample application is presented and future avenues for further research highlighted

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Многоцелевая модель смешанного целочисленного программирования для построения и оптимизации многоэшелонной сети постановок

Застосовується змішане лінійне цілочислове програмування до побудови багатоешелонної мережі поставок (SCN) за допомогою оптимізації перевезень і розподілу в SCN. Запропонована модель дозволяє враховувати багато задач SCN за допомогою розгляду загальних витрат на транспортування і місткості всіх ешелонів. У модель включено три різні цільові функції: перша – мінімізує повні вартості перевезень між усіма ешелонами; друга – мінімізує витрати від збереження і вартості замовлення в центрах розподілу (DCs), а остання цільова функція мінімізує зайву і невикористану потужність заводів і DCs.This paper applies a mixed integer linear programming to designing a multi echelon supply chain network (SCN) via optimizing commodity transportation and distribution of a SCN. Proposed model attempts to aim multi objectives of SCN by considering total transportation costs and capacities of all echelons. The model composed of three different objective functions. The first one is minimizing the total transportation costs between all echelons. Second one is minimizing of holding and ordering costs in distribution centers (DCs) and the last objective function is minimizing the unnecessary and unused capacity of plants and DCs.Применяется смешанное линейное целочисленное программирование к построению многоэшелонной сети поставок (SCN) посредством оптимизации перевозок и распределения в SCN. Предложенная модель позволяет учесть многие задачи SCN посредством рассмотрения общих затрат на транспортировку и емкостей всех эшелонов. В модель включены три различные целевые функции: первая – минимизирует полные стоимости перевозок между всеми эшелонами; вторая – минимизирует затраты от сохранения и стоимости заказа в центрах распределения (DCs), а последняя целевая функция минимизирует излишнюю и неиспользованную способность заводов и DCs

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

The information to share in upstream supply chains dedicated to mass production of customized products for allowing a decentralized management

In an upstream supply chain (USC) dedicated to the mass production of customized products, decentralized management is possible and performing in the steady state, if all the links that precede the final assembly line use periodic replenishment policies. These policies require appropriate safety stocks of alternative or optional components. To achieve such performance in the real world, the supply chain must identify the source of any changes. Unexpected fluctuations in the production of USC plants suggest a bullwhip effect, yet most studies of the bullwhip effect fail to consider build-to-order supply chains. A double transformation of available information, derived from bill of materials explosions and time lags, is required to restore steady-state performance. It then remains to detect and quantify changes and, if a build-to-order strategy of alternative components is possible, use decision rules that are robust to such changes

Power of Automotive Supplier Cluster: The Case of BMW in South Carolina

The phenomenon of regional industrial concentration, or agglomerations, has been studied for more than a century. Over the past couple of decades, interest has dramatically doubled both from the aspects of academics and policy makers. However, the process of making a car requires more sophisticated and complex technology and an upper level of knowledge. The collaboration is indeed an inevitable tool. The agglomeration of the automotive industry in the upper Midwest of the US is one of the most prominent and persistent industrial clusters. Historically, automotive production in the US was dominated by the big three domestic manufacturers, namely: Ford, GM, and Chrysler. However, in the last 30 years, many foreign-owned manufacturers (e.g. Honda, BMW) have opened assembly lines in the South which is far away from the automotive industry center in Michigan (Rosenbaum, 2013). These assemblers were attracted to the South due to the lower rates of unionization and lower labor costs in those states. In this paper, the researcher focus on the competitiveness of this collaboration, if there is any, by using three star analysis and the strength of foreign trade capabilities by Vollrath Analysis

Flexibilitätsbasierte Gestaltung der logistischen Auftragsabwicklung – Anwendung am Beispiel von Produktionsdienstleistern

Zur Bewältigung von Belastungsschwankungen in der industriellen Produktion – der systematischen Regelung von Kapazitätsangebot und -bedarf – existieren Methoden in der logistischen Auftragsabwicklung, deren Anwendungserfolg von den im Produktionsbereich vorhandenen Kapazitäts- und Belastungsflexibilitätsmaß abhängig ist. Die Entwicklung geeigneter Verfahren zur Messung dieser Flexibilitätstypen als auch von Ansätzen zur Nutzung der Messwerte bei der Gestaltung der logistischen Auftragsabwicklung sind die Zielsetzungen dieses Forschungsvorhabens. Vor allem Produktionsdienstleister sind aufgrund ihrer unternehmenstypspezifischen Merkmale für die Validierung der Entwicklungsarbeit sowie die spätere Verwertung der Forschungsergebnisse prädestiniert

E-SCM and inventory management: a study of multiple cases in a segment of the department store chain

Inventory management through the supply chains is a theme that has always enticed managers throughout the world. Due to the increase in market competitiveness and complexity, the traditional statistical models of forecasting demand, based on time series, no longer met the needs imposed on businesses to maintain adequate levels of their inventory and supply interruptions. With the intent to meet these market demands, ERP systems appeared in the 1990's. Nevertheless, even if allowing for a more adequate level of inventory and supply interruptions achieved mainly by the optimization of internal processes and the reduction in lead time, ERP systems did not contribute to reach the SCM's desired levels of inventory that were aimed at by the more competitive businesses. This is because ERP limits itself to an internal analysis of the business. By contrast, inventory management depends on the consumption information (which is external to the business). Aiming to improve even further the level of services delivered to the end consumer, new solutions have been developed, among them the e-SCM, which, since it makes consumption information available in real time, ends up being more dynamic and efficient than the traditional demand forecasting models, Therefore, the present study aims to analyze how the e-SCM can collaborate in maintaining adequate levels of inventory and interruptions in the supply chains. The hypothesis made is that the traditional statistical forecasting models, based on time series and isolatedly, are no longer adequate to adjust the demand, as the tools based on these models do not update the demand in real time and this is fundamental in the current business dynamics. The research method used was the study of multiple cases in a segment of a chain involving a large retailer, its Distribution Center and a supplier of home appliances. For the analysis of the data, the content analysis technique was used. As main results, it was observed that, after the integration of the chain segment by the e-SCM, there was a reduction in the level of the inventory (36.8% in retail and 18% in the industry) and in inventory turnover (from 18.3 to 5.1 days in retail and from 19.6 to 3.2 days in the Distribution Center), aside from the variation in the interruption (from 17.3% to 2.6% in retail and from 3% to 0.1% in the case of the Distribution Center). Therefore, the study brings forth strong indication that the integration of the chain through the e-SCM, may contribute to the SCM's competitiveness.A gestão dos estoques ao longo da cadeia de suprimentos é um tema que sempre instigou gestores por todo o mundo. Com o aumento da competitividade e da complexidade dos mercados, os tradicionais modelos estatísticos de previsão da demanda, fundamentados em séries temporais, não mais atendiam as necessidades impostas às empresas na adequação de seus níveis de estoques e ruptura. No intuito de atender essas exigências do mercado surgem, nos anos 1990, os sistemas ERP. Entretanto, mesmo possibilitando uma adequação nos estoques e na ruptura, levado principalmente pela otimização dos processos internos e redução do lead time, os ERP não contribuíram para que o SCM atingisse o nível de estoque almejado pelas empresas mais competitivas. Isso porque o ERP limita-se a análise interna da empresa. Já a gestão dos estoques depende de informações de consumo (que são externas a empresa). Buscando-se melhorar ainda mais os níveis de serviços prestados ao consumidor final, novas soluções foram desenvolvidas, dentre elas, o e-SCM que por disponibilizar a informação do consumo em tempo real, acaba sendo mais dinâmico e eficiente que os modelos tradicionais de previsão da demanda. Dessa forma, o presente estudo objetiva analisar como o e-SCM pode colaborar para a adequação dos níveis de estoques e ruptura das cadeias de abastecimento. A hipótese defendida é a de que os modelos estatísticos tradicionais de previsão, baseados em séries temporais, isoladamente não são mais adequados para o ajuste da demanda, tendo em vista que ferramentas baseadas nestes modelos não atualizam a demanda em tempo real e isso é fundamental para a atual dinâmica empresarial. O método de pesquisa utilizado foi o estudo de múltiplos casos em um segmento de cadeia que envolve um grande varejista, seu CD e um fornecedor de linha branca. Para análise dos dados, foi utilizada a técnica de análise de conteúdo. Como principais resultados observou-se que, após a integração do segmento de cadeia pelo e-SCM, houve uma redução no nível dos estoques (36,8% no varejo e 18% na indústria) e no giro (de 18,3 para 5,1 dias no varejo e de 19,6 para 3,2 dias no CD), além da variação da ruptura (de 17,3% para 2,6% no varejo e de 3% para 0,1% no caso do CD). Sendo assim, o estudo traz fortes indícios de que a integração da cadeia, por meio do e-SCM, pode colaborar para o aumento da competitividade da SCM

O e-SCM e a gestão dos estoques: um estudo de múltiplos casos em um segmento de cadeia de lojas de departamento

Inventory management through the supply chains is a theme that has always enticed managers throughout the world. Due to the increase in market competitiveness and complexity, the traditional statistical models of forecasting demand, based on time series, no longer met the needs imposed on businesses to maintain adequate levels of their inventory and supply interruptions. With the intent to meet these market demands, ERP systems appeared in the 1990's. Nevertheless, even if allowing for a more adequate level of inventory and supply interruptions achieved mainly by the optimization of internal processes and the reduction in lead time, ERP systems did not contribute to reach the SCM's desired levels of inventory that were aimed at by the more competitive businesses. This is because ERP limits itself to an internal analysis of the business. By contrast, inventory management depends on the consumption information (which is external to the business). Aiming to improve even further the level of services delivered to the end consumer, new solutions have been developed, among them the e-SCM, which, since it makes consumption information available in real time, ends up being more dynamic and efficient than the traditional demand forecasting models, Therefore, the present study aims to analyze how the e-SCM can collaborate in maintaining adequate levels of inventory and interruptions in the supply chains. The hypothesis made is that the traditional statistical forecasting models, based on time series and isolatedly, are no longer adequate to adjust the demand, as the tools based on these models do not update the demand in real time and this is fundamental in the current business dynamics. The research method used was the study of multiple cases in a segment of a chain involving a large retailer, its Distribution Center and a supplier of home appliances. For the analysis of the data, the content analysis technique was used. As main results, it was observed that, after the integration of the chain segment by the e-SCM, there was a reduction in the level of the inventory (36.8% in retail and 18% in the industry) and in inventory turnover (from 18.3 to 5.1 days in retail and from 19.6 to 3.2 days in the Distribution Center), aside from the variation in the interruption (from 17.3% to 2.6% in retail and from 3% to 0.1% in the case of the Distribution Center). Therefore, the study brings forth strong indication that the integration of the chain through the e-SCM, may contribute to the SCM's competitiveness.A gestão dos estoques ao longo da cadeia de suprimentos é um tema que sempre instigou gestores por todo o mundo. Com o aumento da competitividade e da complexidade dos mercados, os tradicionais modelos estatísticos de previsão da demanda, fundamentados em séries temporais, não mais atendiam as necessidades impostas às empresas na adequação de seus níveis de estoques e ruptura. No intuito de atender essas exigências do mercado surgem, nos anos 1990, os sistemas ERP. Entretanto, mesmo possibilitando uma adequação nos estoques e na ruptura, levado principalmente pela otimização dos processos internos e redução do lead time, os ERP não contribuíram para que o SCM atingisse o nível de estoque almejado pelas empresas mais competitivas. Isso porque o ERP limita-se a análise interna da empresa. Já a gestão dos estoques depende de informações de consumo (que são externas a empresa). Buscando-se melhorar ainda mais os níveis de serviços prestados ao consumidor final, novas soluções foram desenvolvidas, dentre elas, o e-SCM que por disponibilizar a informação do consumo em tempo real, acaba sendo mais dinâmico e eficiente que os modelos tradicionais de previsão da demanda. Dessa forma, o presente estudo objetiva analisar como o e-SCM pode colaborar para a adequação dos níveis de estoques e ruptura das cadeias de abastecimento. A hipótese defendida é a de que os modelos estatísticos tradicionais de previsão, baseados em séries temporais, isoladamente não são mais adequados para o ajuste da demanda, tendo em vista que ferramentas baseadas nestes modelos não atualizam a demanda em tempo real e isso é fundamental para a atual dinâmica empresarial. O método de pesquisa utilizado foi o estudo de múltiplos casos em um segmento de cadeia que envolve um grande varejista, seu CD e um fornecedor de linha branca. Para análise dos dados, foi utilizada a técnica de análise de conteúdo. Como principais resultados observou-se que, após a integração do segmento de cadeia pelo e-SCM, houve uma redução no nível dos estoques (36,8% no varejo e 18% na indústria) e no giro (de 18,3 para 5,1 dias no varejo e de 19,6 para 3,2 dias no CD), além da variação da ruptura (de 17,3% para 2,6% no varejo e de 3% para 0,1% no caso do CD). Sendo assim, o estudo traz fortes indícios de que a integração da cadeia, por meio do e-SCM, pode colaborar para o aumento da competitividade da SCM

A multi-objective mixed integer programming model for multi echelon supply chain network design and optimization

This paper applies a mixed integer linear programming to designing a multi echelon supply chain network (SCN) via optimizing commodity transportation and distribution of a SCN. Proposed model attempts to aim multi objectives of SCN by considering total transportation costs and capacities of all echelons. The model composed of three different objective functions. The first one is minimizing the total transportation costs between all echelons. Second one is minimizing of holding and ordering costs in distribution centers (DCs) and the last objective function is minimizing the unnecessary and unused capacity of plants and DCs.Застосовується змішане лінійне цілочислове програмування до побудови багатоешелонної мережі поставок (SCN) за допомогою оптимізації перевезень і розподілу в SCN. Запропонована модель дозволяє враховувати багато задач SCN за допомогою розгляду загальних витрат на транспортування і місткості всіх ешелонів. У модель включено три різні цільові функції: перша — мінімізує повні вартості перевезень між усіма ешелонами; друга — мінімізує витрати від збереження і вартості замовлення в центрах розподілу (DCs), а остання цільова функція мінімізує зайву і невикористану потужність заводів і DCs.Применяется смешанное линейное целочисленное программирование к построению многоэшелонной сети поставок (SCN) посредством оптимизации перевозок и распределения в SCN. Предложенная модель позволяет учесть многие задачи SCN посредством рассмотрения общих затрат на транспортировку и емкостей всех эшелонов. В модель включены три различные целевые функции: первая — минимизирует полные стоимости перевозок между всеми эшелонами; вторая — минимизирует затраты от сохранения и стоимости заказа в центрах распределения (DCs), а последняя целевая функция минимизирует излишнюю и неиспользованную способность заводов и DCs