Sub-Saharan African countries present chronic energy shortages and heavy reliance on oil imports for diesel. The small demand and high production costs in some countries have compromised the economic feasibility of the biodiesel industry in the region. Therefore, to overcome these limitations a model of “multi-countries” cooperated production and consumption of biodiesel was proposed for a group of seven neighboring countries. The model explored linear programming and simulations to the problem of minimizing biodiesel production costs considering different types of production and demand restrictions. The data processing was realized using the Solver and Linear Interactive Discrete Optimizer software (LINDO). The simulations and scenarios revealed that palm oil is the crop that minimize the production costs (US$0.82/L) and that, although jatropha was classified in the second place (US$1.05/L), it is the crop with the biggest job creation potential (5.0 times that of the palm oil seeds). These results reveal the presence of a trade-off in the strategy and the choice between different oilseeds: (a) to produce biodiesel from the crop with minimal costs (palm oil) or (b) to choose the one that has the biggest potential for job creation (jatropha). Considering the diesel price between US$0.60 and US$1.14/L at service stations in the region in 2016, both the biodiesel from palm oil and jatropha will need subsidies and fiscal incentives (tax reductions) to be competitive in the fuel market (diesel). The volume of biodiesel to supply the B10 demand in 2031 has the potential to reduce US$ 1.98 billion/year of the expenses on oil imports. It is worth observing that this decision-support model adds the “multi-countries” cooperation perspective as a contribution to the methodological and political approaches about biofuels production and consumption and can be exploited as a starting point for the formulation of policies, strategies, and investment decisions for the establishment of biodiesel production programs.

A representação do tráfego de trens em estudos de simulação é uma tarefa complexa, que exige conhecimentos específicos das operações ferroviárias. De ...

O presente artigo avalia a infraestrutura portuária da Bahia, apresentando diagnóstico e perspectivas de seus portos e terminais privados, destacando sua movimentação de cargas com evidências de necessária ampliação da capacidade de parte dessas instalações, diante da elevada taxa de utilização destas. O Complexo Portuário da Bahia, constituído de três portos públicos e sete terminais, encontra-se predominantemente instalado na Baía de Todos-os-Santos, porto natural, configurando-se como um dos mais importantes cluster de apoio transporte marítimo nacional. Revelam-se as vantagens de suas aquavias e as limitações dos modais rodo-ferroviário para atendimento à supply chain destas instalações. Contribuindo para as análises de opções de ampliação da capacidade, desenvolve-se modelo matemático de teoria de filas com o objetivo de avaliar o estado atual da fila de navios de seu único terminal de contêiner (TECON), empregando-se os softwares R e QSB+, bem como avalia-se a recomendação da Associação de Usuários de Portos – USUPORT, que propõe a construção de novo terminal, cuja capacidade atenderia em quase cinco vezes a atual movimentação de contêineres. Os resultados desta modelagem revelam as limitações desta proposta, em relação ao impacto gerado no Porto de Salvador e seu entorno, em termos de fluxo de veículos, bem como ao provável aumento de emissões gasosas (NOx).

O presente trabalho consiste em uma proposta de metodologia para futura representação do transporte ferroviário de cargas de minério de ferro a partir de mi...

The availability of rail infrastructure resources is a major driver of rail operations performance. To evaluate the impact of infrastructure provision, network simulation models can be used to accurately represent train traffic behavior in a wide range of scenarios. However, performing this task can result in a problem of high combinatorial nature as the number of factors and their associated levels increase. This requires more sophisticated techniques such as experimental design formulations or optimization modeling in order to yield satisfactory results. Yet the research in network simulation models for rail systems has hitherto been limited to simple what-if analysis, made up from few factors that cannot represent the whole spectrum of interventions. This is especially critical in closed-loop rail systems where trains are subject to various interferences. Local improvements can be misleading as the queues are merely transferred within the network. Considering this, we propose a hybrid simulation-optimization model to aid the strategic decision of minimizing supplementary capital costs in a heavy-haul Brazilian railroad under construction. As soon as the railroad is completed, investments in both loading and unloading rail terminals will be necessary. First, we developed a representative and flexible model capable of dealing with complex relations between variable infrastructure provision and the resulting operational performance. Then, we simulated this system to prove that the current set of proposed infrastructure resources cannot meet the transportation demands. Afterwards, we demonstrate that local improvements can be delusive as the queues are shifted from loading to unloading operations, reciprocally. Then, we solve an optimization model to define the minimal supplementary investment in order to meet the commercial goals of mining companies. This is done by choosing the best trackage configuration, equipment quantity and capacity and fleet sizing in 3 different production scenarios. The best values of the objective function were found by improving both loading and unloading equipment and increasing the number of trains.