Considering supply risk for supplier selection using an integrated framework of data envelopment analysis and neural networks

For many years, supplier selection as an important multi-criteria decision has attracted both the researchers and practitioners. Recently, high incidences of natural disasters, terrorism attacks, labor strikes, and other kinds of risks, also known as disruptions, indicate the vulnerability of procurement process to these unpredicted events. In this study, a new framework is introduced to select suppliers while considering the supply risks. In the proposed framework, an expert is asked to determine the reliability of each procurement element (i.e., production, transportation, and communication) based on some proposed risk factors. Then, a distinct Multi-Layer Perceptron (MLP) network is trained to play the role of the expert opinion for estimating the reliability scores of each procurement. In addition to reliabilities, the Data Envelopment Analysis (DEA) is used to take into account the conventional selection criteria: price, delivery, quality, and capacity. A set of Pareto-optimal suppliers is obtained from the combination of efficiencies and reliability scores. Finally, the decision maker is recommended to choose between the non-dominated suppliers. Obtained experiment results indicate the effectiveness of the proposed framework

Performance Assessment of Brazilian Power Transmission and Distribution Segments using Data Envelopment Analysis

In this study, we conducted efficiency analyzes of both power transmission and distribution segments in Brazilian electricity sector. In order to accomplish these analyzes, DEA-VRS models, cost analysis and Window Analysis (WA) approaches were carried out. The results showed that overall efficiency and stability in the distribution sector are higher than in transmission sector, which suggest that distribution companies are better managed regarding their operational costs compared to those within transmission segment. Moreover, it was accounted that approximately R$ 21 billion could have been saved if DMUs (within distribution and transmission systems) analyzed had operated with maximum level of efficiency from 2008 to 2014. Consequently, energy tariff prices paid by each consumer could have also been lower. Keywords: Data Envelopment Analysis; Window Analysis; Power transmission and distribution segments JEL Classifications: C14; C38; O1

Performance assessment of Brazilian power transmission and distribution segments using data envelopment analysis.

In this study, we conducted efficiency analyzes of both power transmission and distribution segments in Brazilian electricity sector. In order to accomplish these analyzes, data envelopment analysis-variable returns to scale models, cost analysis and window analysis approaches were carried out. The results showed that overall efficiency and stability in the distribution sector are higher than in transmission sector, which suggest that distribution companies are better managed regarding their operational costs compared to those within transmission segment. Moreover, it was accounted that approximately R$ 21 billion could have been saved if decision making units (within distribution and transmission systems) analyzed had operated with maximum level of efficiency from 2008 to 2014. Consequently, energy tariff prices paid by each consumer could have also been lower

Análise de desempenho de Empresas de distribuição de Energia Elétrica utilizando DEA e REA.

O setor de distribuição de energia elétrica no Brasil apresenta características de monopólio natural e, portanto, necessita de forte regulamentação econômica. O mecanismo adotado para regulamentação tarifária é a Revisão Tarifária Periódica (RTP), realizada pela Agência Nacional de Energia Elétrica (ANEEL). A RTP tem o papel de garantir que a energia elétrica seja fornecida com qualidade aos consumidores e que os investimentos e os custos operacionais sejam compatíveis para que se tenham tarifas justas tanto para o concessionário como para o cliente. Este trabalho foca em um dos desafios do processo de RTP que é a determinação dos custos operacionais eficientes das concessionárias de distribuição, mais especificamente, na análise de eficiência das distribuidoras. O documento traz uma visão geral do terceiro e quarto ciclo de RTP no Brasil bem como a experiência internacional acerca do tema. Como base metodológicas, o trabalho faz uso de duas técnicas de benchmarking: o Data Envelopment Analysis (DEA) e o Ratio-based Efficiency Analysis (REA). O DEA é a metodologia vigente, baseada no conceito de fronteira de eficiência, adotada pela ANEEL para a análise de eficiência das distribuidoras. O REA é apresentado como uma alternativa de metodologia a ser aplicada ao setor. Ele é baseado não somente no conceito de fronteira de eficiência, mas também na comparação aos pares e eficiências relativas, trazendo, portanto, uma maior riqueza à análise. O REA faz uma avaliação da homogeneidade dos conjuntos e, como as características das áreas de concessão das distribuidoras brasileiro são bem heterogêneas, a aplicação do REA pode auxiliar, por exemplo, no estabelecimento das restrições de limites aos pesos. Os limites aos pesos vêm sendo aplicado na regulação da transmissão desde o 3º CRTP e foi adicionado ao segmento da distribuição no 4º CRTP na tentativa de homogeneizar a amostra de distribuidoras. Esta limitação aos pesos gerou questionamentos, pois a forma como os mesmos foram estabelecidos não foi divulgada pela ANEEL. Este trabalho faz uma avaliação do impacto da utilização destes limites e sua aderência ao modelo brasileiro, considerando a base de dados do 4º CRTP

Robust optimization in data envelopment analysis: extended theory and applications.

Performance evaluation of decision-making units (DMUs) via the data envelopment analysis (DEA) is confronted with multi-conflicting objectives, complex alternatives and significant uncertainties. Visualizing the risk of uncertainties in the data used in the evaluation process is crucial to understanding the need for cutting edge solution techniques to organizational decisions. A greater management concern is to have techniques and practical models that can evaluate their operations and make decisions that are not only optimal but also consistent with the changing environment. Motivated by the myriad need to mitigate the risk of uncertainties in performance evaluations, this thesis focuses on finding robust and flexible evaluation strategies to the ranking and classification of DMUs. It studies performance measurement with the DEA tool and addresses the uncertainties in data via the robust optimization technique. The thesis develops new models in robust data envelopment analysis with applications to management science, which are pursued in four research thrust. In the first thrust, a robust counterpart optimization with nonnegative decision variables is proposed which is then used to formulate new budget of uncertainty-based robust DEA models. The proposed model is shown to save the computational cost for robust optimization solutions to operations research problems involving only positive decision variables. The second research thrust studies the duality relations of models within the worst-case and best-case approach in the input \u2013 output orientation framework. A key contribution is the design of a classification scheme that utilizes the conservativeness and the risk preference of the decision maker. In the third thrust, a new robust DEA model based on ellipsoidal uncertainty sets is proposed which is further extended to the additive model and compared with imprecise additive models. The final thrust study the modelling techniques including goal programming, robust optimization and data envelopment to a transportation problem where the concern is on the efficiency of the transport network, uncertainties in the demand and supply of goods and a compromising solution to multiple conflicting objectives of the decision maker. Several numerical examples and real-world applications are made to explore and demonstrate the applicability of the developed models and their essence to management decisions. Applications such as the robust evaluation of banking efficiency in Europe and in particular Germany and Italy are made. Considering the proposed models and their applications, efficiency analysis explored in this research will correspond to the practical framework of industrial and organizational decision making and will further advance the course of robust management decisions

Robust optimization in data envelopment analysis: extended theory and applications.

Performance evaluation of decision-making units (DMUs) via the data envelopment analysis (DEA) is confronted with multi-conflicting objectives, complex alternatives and significant uncertainties. Visualizing the risk of uncertainties in the data used in the evaluation process is crucial to understanding the need for cutting edge solution techniques to organizational decisions. A greater management concern is to have techniques and practical models that can evaluate their operations and make decisions that are not only optimal but also consistent with the changing environment. Motivated by the myriad need to mitigate the risk of uncertainties in performance evaluations, this thesis focuses on finding robust and flexible evaluation strategies to the ranking and classification of DMUs. It studies performance measurement with the DEA tool and addresses the uncertainties in data via the robust optimization technique. The thesis develops new models in robust data envelopment analysis with applications to management science, which are pursued in four research thrust. In the first thrust, a robust counterpart optimization with nonnegative decision variables is proposed which is then used to formulate new budget of uncertainty-based robust DEA models. The proposed model is shown to save the computational cost for robust optimization solutions to operations research problems involving only positive decision variables. The second research thrust studies the duality relations of models within the worst-case and best-case approach in the input – output orientation framework. A key contribution is the design of a classification scheme that utilizes the conservativeness and the risk preference of the decision maker. In the third thrust, a new robust DEA model based on ellipsoidal uncertainty sets is proposed which is further extended to the additive model and compared with imprecise additive models. The final thrust study the modelling techniques including goal programming, robust optimization and data envelopment to a transportation problem where the concern is on the efficiency of the transport network, uncertainties in the demand and supply of goods and a compromising solution to multiple conflicting objectives of the decision maker. Several numerical examples and real-world applications are made to explore and demonstrate the applicability of the developed models and their essence to management decisions. Applications such as the robust evaluation of banking efficiency in Europe and in particular Germany and Italy are made. Considering the proposed models and their applications, efficiency analysis explored in this research will correspond to the practical framework of industrial and organizational decision making and will further advance the course of robust management decisions

Análises inter e intradistribuidoras para gerenciamento de recursos no ganho de eficiência

The electricity distribution sector in Brazil has the characteristic of a natural monopoly and needs economic regulation. The mechanism adopted for tariff regulation is the Periodic Tariff Review (RTP), carried out by the National Regulatory Agency. Currently, the efficiency analysis method applied at RTP is the Data Envelopment Analysis (DEA), already used by other countries in the evaluation of efficiency in energy utilities. Utilities classified as inefficient by the DEA must direct their efforts to win efficiency by looking at practices from the utilities classified by efficient by the DEA. This study proposes an efficiency analysis focused on improving the current methodology at RTP and suggests tools that may be useful in providing strategies to improve efficiency. The analyzes presented here focus on two levels: sectorial and corporate. At the sectorial level, an efficiency analysis is proposed, in which each utility is considered as a Decision-Making Unit (DMU) in the DEA and compared with each other. This efficiency analysis between utilities delimited the database defined by the regulator. The study also applies the concept of 'clustering' the set of DMUs by the k-means method, showing the effect that a reduction of DMUs` set causes in the efficiency analysis. Finally, the impact of DEA efficiency is measured quantitatively on the utilities' regulatory operating costs (COR). At the corporate level, an innovative internal benchmarking is proposed, named here self-efficiency analysis. This analysis splits the utility into smaller parts (regional), and these parts are considered the DMUs in the DEA. The idea of splitting the concession area into smaller areas is to incorporate the effect of environmental characteristics (such as lightning incidence and vegetation height) in the efficiency analysis. The thesis presents a case study for a utility in São Paulo. The self-efficiency analysis, therefore, defines efficiency gain strategy by indicating the most inefficient areas inside the utility. The study also applies two other benchmarking techniques, the Cross-efficiency Analysis and the Ratio-based Efficiency Analysis. The CEA and REA studies bring new efficiency indicators for efficiency analysis between utilities and self-efficiency analysis.O setor de distribuição de energia elétrica no Brasil apresenta características de monopólio natural e, portanto, necessita de regulamentação econômica. O mecanismo adotado para regulamentação tarifária é a Revisão Tarifária Periódica (RTP), realizada pela Agência Nacional de Energia Elétrica (ANEEL). Atualmente a metodologia de análise de eficiência aplicada na RTP é o Data Envelopment Analysis (DEA) que busca comparar as práticas das concessionárias de distribuição de energia elétrica. As distribuidoras consideradas ineficientes, pelo DEA, devem direcionar seus esforços de ganho de eficiência sob as práticas gerenciais das distribuidoras eficientes. Este estudo sugere melhorias na metodologia vigente para análise de eficiência e sugere ferramentas que venham a ser úteis na definição de uma estratégia de ganho de eficiência. As análises apresentadas podem ser divididas em duas vertentes: setorial e corporativa. A vertente setorial sugere uma análise entre as distribuidoras reguladas pela ANEEL, nomeado de análise interdistribuidoras, na qual cada distribuidora é considerada como uma Decision Making Unit (DMU) no DEA. A análise interdistribuidoras realiza estudos considerando a base de dados definida pela ANEEL. O estudo também aplica o conceito de ‘clusterização’ do conjunto de DMUs pelo método k-means, para mostrar o efeito que a redução do conjunto de DMUs causa na análise de eficiência. Por fim, o impacto da eficiência do DEA é medido quantitativamente nos custos operacionais regulatórios (COR) das distribuidoras. A vertente corporativa sugere de forma inovadora um benchmarking interno, nomeado de análise intradistribuidora. Nesta análise a distribuidora é dividida em partes menores (regionais) e estas regionais são consideradas como as DMUs no DEA. A ideia de repartir a área de concessão em áreas menores é incorporar o efeito das características ambientais, como incidência de raios e altura de vegetação, na análise de eficiência. A tese apresenta um estudo de caso para uma distribuidora de São Paulo. A análise intradistribuidora também tem objetivo de auxiliar na estratégica de ganho de eficiência ao apontar as regiões mais ineficientes da distribuidora. O estudo, também, aplica outras duas técnicas de benchmarking, a Cross-efficiency Analysis (CEA) e a Ratio-based Efficiency Analysis (REA). O estudo do CEA e REA traz novos indicadores de eficiência tanto para análise interdistribuidoras como a análise intradistribuidora