Insight into single- and bi-objective optimization of industrial problems

ABSTRACT

Evolutionary single- and bi-objective optimization of industrial problems, namely, naphtha cracking and styrene reactor are considered. Bi-objective optimization is solved using the HMODE-DLS algorithm, whereas an improved black hole optimizer (BHO) is employed for the single-objective optimization (SOO) problem. For the naphtha cracking process, ethylene selectivity (S_E) and severity index (SI) are selected as objectives. Similarly, styrene selectivity (S_ST) and styrene flow rates (F_ST) are considered objectives for styrene reactor. Pareto ranking is carried out by using the net flow method (NFM) and the best solution is compared with the single- and multi-objective optimization results. In a single objective optimization study, the optimum solution corresponds to the lowest value of the SI (1.571) at the cost of the worst value of S_E (0.269). Similarly, the highest values of F_ST (16.642 kmol/h) and S_ST (96.158%) are resulted in the SOO study of styrene reactor.

KEYWORDS:

• Styrene
• naphtha cracking
• optimization
• Pareto ranking
• NFM
• stochastic
• evolutionary

Disclosure statement

No potential conflict of interest was reported by the author.