Abstract
AbstractIn this research, the optimal feed flowrate trajectories, and reaction temperature for autocatalytic esterification of sec-butyl propionate in the semi-batch reactor had been determined using dynamic-nonlinear programming (NLP) based optimization. The dynamic multi-objective optimization (DMOO) problem yielded from this autocatalytic esterification due to contrary objective functions. The DMOO problem was characterized by multiple solutions, which are non-dominated or Pareto solutions. In this work, to generate the Pareto solutions for the chosen objective functions, which maximize conversion and minimize process time, the ε-constraint approach and control vector parameterization (CVP) has been applied. Here, various combinations of conversion and process time were obtained as a result of different optimal temperatures and feed flowrates in each point of Pareto solutions. Finally, these solution methods could benefit industries in evaluating and selecting the trade-offs and operating policies.KeywordsDynamic optimizationMulti-objective optimizationAutocatalytic esterification
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