A state of art review on applications of multi-objective evolutionary algorithms in chemicals production reactors

Zainab Al Ani, Ashish M. Gujarathi*, Ala’a H. Al-Muhtaseb

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Chemical reactors are employed to produce several materials, which are utilized in numerous applications. The wide use of these chemical engineering units shows their importance as their performance vastly affects the production process. Thus, improving these units will develop the process and/or the manufactured material. Multi-objective optimization (MOO) with evolutionary algorithms (EA’s) has been used to solve several real world complex problems for improving the performance of chemical reactors with conflicting objectives. These objectives are of different nature as they could be economy, environment, safety, energy, exergy and/or process related. In this review, a brief description for MOO and EA’s and their several types and applications is given. Then, MOO studies, which are related to the materials’ production via chemical reactors, those were conducted with EA’s are classified into different classes and discussed. The studies were classified according to the produced material to hydrogen and synthesis gas, petrochemicals and hydrocarbons, biochemical, polymerization and other general processes. Finally, some guidelines are given to help in deciding on future research.

Original languageEnglish
JournalArtificial Intelligence Review
Publication statusAccepted/In press - 2022


  • Chemical reactors
  • Differential Evolution
  • Evolutionary algorithms
  • Genetic algorithms
  • Industrial Applications
  • Review

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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