Interactive Multiobjective Optimization

Many optimization problems have multiple objectives and these objectives are typically conflicting in nature. Because of the conflicting nature, there typically does not exist a single optimal solution but, rather, several so-called Pareto optimal (PO) solutions. The set of all Pareto optimal solutions in the objective space is called a Pareto front. To gain the greatest insight in to the problem it is necessary to consider all relevant objectives, which easily leads to many-objective optimization problems, (i.e. more than three objectives).This article introduces, and argues the advantages of using, interactive multi-objective optimization, especially the synchronous NIMBUS method for handling many-objective optimization problems as against other widely-used evolutionary multi-objective optimization algorithms

Document Details

AuthorSindhya. K
TypeMagazine Article
Date 1st July 2017


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