ABSTRACT Cross docking is a form of operating break-bulk freight terminals in which the receiving products are not stocked but, instead, the incoming cargo is internally transferred to be immediately shipped in distribution trucks. With this approach, inventory costs and lead-times are significantly reduced. In this work, an approximate, continuous, non-stationary queueing model is established to estimate the number of cargo discharging doors in the receiving dock. Since the traditional first-come, first-served queueing discipline is not applicable to this specific problem, an alternative formulation, called least-distance, firstserved queue discipline, is adopted and analysed with a simulation approach. The problem is modelled to support a preliminary design of a cross-dock terminal. The objective function, to be minimized, is the sum of the rent cost of the terminal facility, the waiting cost of inbound trailers when being attended at the terminal, and the cost of handling and moving freight inside the terminal.

Governments of many developing countries are presently granting concessions to private organizations to operate container terminals. A key element in this process is the technical and economic evaluation of the project. In practice, the demand levels over time are volatile. The first part of the paper deals with a capacity expansion problem with stochastic demand. Next, an optimization model employs a dynamic programming routine to find the best epochs to install new berths. Ship waiting times are computed with queuing models and are introduced into the main model as upper restrictions based on international practice. Finally, a real options analysis is performed with the objective of evaluating the effects of an eventual abandonment of the project at a pre-defined time horizon. The model is then applied to the container terminal of the Port of Rio Grande, Brazil.

A análise de produtividade é ferramenta importante para a tomada de decisão e para a gestão de organizações, possibilitando avaliar os efeitos dos inputs na obtenção de níveis desejados de outputs. A Análise Envoltória de Dados (DEA) é um método não paramétrico baseado em fronteiras lineares por partes ajustadas através de programação matemática e utilizada para analisar as eficiências técnica, de escala e de gestão de empresas de ônibus que operam nas ligações interestaduais no Brasil (ISBT). Os dados foram obtidos no web-site da Agência Nacional de Transportes Terrestres (ANTT). Como os fatores de produção são restritos por razões técnicas e operacionais, restrições de pesos foram introduzidas nos modelos. A análise mostrou três grupos de empresas não eficientes, com claras diferenças de produtividade. Também são calculadas as eficiências de gestão relativas a esses três grupos. Finalmente é apresentado um exemplo de benchmarking de uma empresa não eficiente através de DEA.

Productivity analysis is an important policy making and managerial control tool for assessing the degree to which inputs are utilized in the process of obtaining desired outputs. Data Envelopment Analysis (DEA) is a non-parametric method based on piecewise linear frontiers estimated with the aid of mathematical programming techniques and used, in this paper, to investigate technical, scale and managerial efficiencies associated with interstate bus companies in Brazil (ISBT). Data has been obtained from the web-site of the Brazilian National Agency of Land Transportation (ANTT). Since production factors in the application are constrained by technical and operational reasons, weight restrictions were introduced into the DEA models. The analysis has shown three groups of non-efficient bus firms, with clear differences in productivity. The relative managerial efficiencies of the firms in the non-efficient groups were also computed and analyzed. Finally, an example of benchmarking a non-efficient firm with DEA is presented.

Os sistemas de metrô são parte relevante do transporte em muitas cidades do globo. Um aspecto importante da política de transportes é a oferta. Nesse contexto, é de interesse verificar se os operadores estão trabalhando de maneira eficiente, em termos técnicos, e no que diz respeito a ganhos de escala. A análise do processo de produção de metrôs tem sido realizada através de estudos econométricos baseados em práticas tecnológicas médias. Um método mais recente para estudar fronteiras de produção é a Análise Envoltória de Dados (DEA). Trata-se de um método não-paramétrico, mas suas aplicações a metrôs, que envolvem relações mais rígidas entre as variáveis tecnológicas, requerem uma análise prévia dos inputs e dos outputs. DEA é utilizada no artigo para analisar a eficiência e ganhos de escala de 21 metrôs. É também utilizada como instrumento auxiliar no benchmarking de metrôs não eficientes, com ênfase ao metrô de São Paulo

Rapid-transit services are a relevant part of the transportation network in most cities of the world. An important aspect of transport policy is the supply of public urban transportation. In particular, it is of interest to determine whether rapid-transit operators are working in a technically and scale-efficient way. Production analysis of transit services has been characterized by the econometric study of average practice technologies. A more recent method to study such production frontiers is Data Envelopment Analysis (DEA). It is a non-parametric method, but its application to rapid-transit, where the relations among technological variables are more strict, requires a previous structural analysis of the intervening inputs and outputs. DEA is employed in this paper to investigate the efficiency and returns to scale of 21 rapid-transit properties of the world. DEA was also used for the benchmarking of non-efficient rapid-transit properties, with special emphasis to the São Paulo’s subway system