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Local Search with Quadratic Approximations into Memetic Algorithms for Optimization with Multiple Criteria

This research contributed to a successful €287,700 EU grant to support a 4-year International Research Staff Exchange Scheme (2012-2015), “New Horizons for Multi Criteria Decision Making” (Project No.: 295152). The complexity of many industrial applications of multiobjective optimization results in the applications being resource-constrained, especially since they often require computationally expensive function evaluations. This paper describes a hybrid method that integrates an evolutionary optimization with local search. The method improves the quality of solutions without recourse to additional function evaluations, thereby alleviating these resource constraints.