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

Ashish M. Gujarathi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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 (SE) and severity index (SI) are selected as objectives. Similarly, styrene selectivity (SST) and styrene flow rates (FST) 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 SE (0.269). Similarly, the highest values of FST (16.642 kmol/h) and SST (96.158%) are resulted in the SOO study of styrene reactor.

Original languageEnglish
Pages (from-to)1874-1880
Number of pages7
JournalMaterials and Manufacturing Processes
Issue number15
Publication statusPublished - Mar 13 2023


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

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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