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Sensitivity of performance evaluation results by inverted generational distance to reference points.

, , и . CEC, стр. 1107-1114. IEEE, (2016)

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Hiroyuki Tan

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Hiroyuki Isobe

 

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Common properties of scalable multiobjective problems and a new framework of test problems., , и . CEC, стр. 3011-3018. IEEE, (2016)Sensitivity of performance evaluation results by inverted generational distance to reference points., , и . CEC, стр. 1107-1114. IEEE, (2016)Algorithm structure optimization by choosing operators in multiobjective genetic local search., , , , и . CEC, стр. 854-861. IEEE, (2015)Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes., , , и . IEEE Trans. Evol. Comput., 21 (2): 169-190 (2017)Relation Between Weight Vectors and Solutions in MOEA/D., , , и . SSCI, стр. 861-868. IEEE, (2015)Modified Distance Calculation in Generational Distance and Inverted Generational Distance., , , и . EMO (2), том 9019 из Lecture Notes in Computer Science, стр. 110-125. Springer, (2015)Distance-Based Analysis of Crossover Operators for Many-Objective Knapsack Problems., , , и . PPSN, том 8672 из Lecture Notes in Computer Science, стр. 600-610. Springer, (2014)Visual examination of the behavior of EMO algorithms for many-objective optimization with many decision variables., , и . IEEE Congress on Evolutionary Computation, стр. 2633-2640. IEEE, (2014)Meta-level multi-objective formulations of set optimization for multi-objective optimization problems: multi-reference point approach to hypervolume maximization., , и . GECCO (Companion), стр. 89-90. ACM, (2014)A Study on Performance Evaluation Ability of a Modified Inverted Generational Distance Indicator., , и . GECCO, стр. 695-702. ACM, (2015)