Hierarchical Representation Based Constrained Multi-objective Evolutionary Optimisation of Molecular Structures
Authors
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Gyula Dörgő
Affiliation
MTA-PE Lendület Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, H-8200 Veszprém, P.O.B. 158, Hungary
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János Abonyi
AffiliationMTA-PE Lendület Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, H-8200 Veszprém, P.O.B. 158, Hungary
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.
