Hierarchical representation based constrained multi-objective evolutionary optimisation of molecular structures

Gyula Dörgő, J. Abonyi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose an efficient algorithm to generate Pareto optimal set of reliable molecular structures represented by group contribution methods. To effectively handle structural constraints we introduce goal oriented genetic operators to the multi-objective Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The constraints are defined based on the hierarchical categorisation of the molecular fragments. The efficiency of the approach is tested on several benchmark problems. The proposed approach is highly efficient to solve the molecular design problems, as proven by the presented benchmark and refrigerant design problems.

Original languageEnglish
Pages (from-to)210-225
Number of pages16
JournalPeriodica Polytechnica Chemical Engineering
Volume63
Issue number1
DOIs
Publication statusPublished - Jan 1 2019

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Keywords

  • Genetic operators
  • Hierarchical constraints
  • Similarity of pareto fronts
  • Structural optimisation

ASJC Scopus subject areas

  • Chemical Engineering(all)

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