Abstract
The aim of this study is to present a mixed-integer multi-objective optimization model to indicate investment in new petrochemical units over a given period, so that the total cost of a petrochemical industry and a risk function are the functions to be minimized. The Brazilian petrochemical industry is used as a case study to illustrate the application of the multi-objective optimization model. It is noticeable that fifteen polymerization processes, as Nylon 6 and polyether polyol, are selected for investment in new process units in all scenarios. Also, model solutions suggest that some petrochemicals, such as p-xylene, should be produced by two different chemical processes, so that a trade-off between cost and risk is maintained. In general, results indicated that the model can be used to support the decision-making process in assessing investment in new petrochemical plants, in order to reduce the risk and the total cost of the petrochemical industry.
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