Approximation method for computationally expensive nonconvex multiobjective optimization problems
Published inJyväskylä studies in computing
PublisherUniversity of Jyväskylä
monitavoiteoptimointi Pareto-optimointi Pareto-tehokkuus laskennallinen vaativuus multiobjective optimization computational cost computational efficiency Pareto front approximation surrogate function interactive decision making decision maker psychological convergence Pareto dominancy Pareto optimality päätöksenteko optimointi menetelmät laskennalliset menetelmät approksimointi
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On solving computationally expensive multiobjective optimization problems with interactive methods Ojalehto, Vesa (University of Jyväskylä, 2014)
Tabatabaei, Seyed Mohammad Mehdi (University of Jyväskylä, 2016)In this thesis, we consider solving computationally expensive multiobjective optimization problems that take into account the preferences of a decision maker (DM). The aim is to support the DM in identifying the most ...
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A Surrogate-assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-objective Optimization Chugh, Tinkle; Jin, Yaochu; Miettinen, Kaisa; Hakanen, Jussi; Sindhya, Karthik (Institute of Electrical and Electronics Engineers, 2018)We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for computationally expensive optimization problems with more than three objectives. The proposed algorithm is based on a recently developed ...
Chugh, Tinkle (University of Jyväskylä, 2017)Multiobjective optimization problems (MOPs) with a large number of conﬂicting objectives are often encountered in industry. Moreover, these problem typically involve expensive evaluations (e.g. time consuming simulations ...