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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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 ...
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