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- W2994657572 abstract "In this contribution, a unique multi-objective mixed-integer dynamic optimization problem considering two conflicting objectives, namely, maximization of amount of product per dollar while minimizing CO2 emission is formulated and solved using the elitist non-dominated genetic algorithm for both conventional batch distillation (CBD) and vapor recompressed batch distillation (VRBD) operating at constant reflux mode. Here, selection of an optimal solution from the Pareto-optimal front is performed by 10 Pareto ranking methods along with entropy weighting. A wide boiling separating system (i.e., acetone and water) is adopted for illustrating the proposed multi-objective optimization of batch distillation. Two separate optimization studies for CBD and VRBD are conducted with the target of either improving an existing plant or setting up a new plant. Results obtained show that most of the popular Pareto ranking methods select same optimal solution for each of these problems. Finally, a comparative analysis is performed to find the benefits of vapor recompression over the conventional scheme." @default.
- W2994657572 created "2019-12-26" @default.
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- W2994657572 date "2020-02-01" @default.
- W2994657572 modified "2023-10-17" @default.
- W2994657572 title "Mixed-Integer dynamic optimization of conventional and vapor recompressed batch distillation for economic and environmental objectives" @default.
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- W2994657572 doi "https://doi.org/10.1016/j.cherd.2019.12.006" @default.
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