In this work the performance of an industrial hydrogen plant is improved by
multi-objective optimization using an adaptation of the nondominated sorti
ng genetic algorithm (NSGA). The heat flux profile on the steam reformer tu
bes is treated as a decision variable, yielding optimal heat flux profiles
for each Pareto solution. The optimization problem has been considered both
as a two and three-objective problem. For a fixed feed rate of methane to
the unit, simultaneous maximization of product hydrogen and export steam fl
ow rates are considered as the two objectives. The results are better than
those obtained in an earlier work by Rajesh et al. (2001), with flue gas te
mperature in place of the heat flux profile as a decision variable. Minimiz
ation of reformer duty was chosen to be the third objective. More useful in
formation is available for the optimal operation of hydrogen plants from th
ree-objective optimization, even though computational time for two and thre
e objectives is comparable.