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Titlebook: Evolutionary Multi-Criterion Optimization; 6th International Co Ricardo H. C. Takahashi,Kalyanmoy Deb,Salvatore Gr Conference proceedings 2

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樓主: retort
21#
發(fā)表于 2025-3-25 06:01:53 | 只看該作者
Very Large-Scale Neighborhood Search for Solving Multiobjective Combinatorial Optimization ProblemsSNS are proposed for these two problems and are integrated into the two-phase Pareto local search. The results obtained on biobjective instances outperform the state-of-the-art results for various indicators.
22#
發(fā)表于 2025-3-25 09:07:26 | 只看該作者
Statistical tests for related designs,edominantly present in most trade-off solutions, can be considered as the characteristic features of the Pareto-optimal front. Knowledge of such features, in addition to providing better insights to the problem, enables the designer to handcraft solutions for other optimization tasks which are struc
23#
發(fā)表于 2025-3-25 14:20:14 | 只看該作者
24#
發(fā)表于 2025-3-25 16:09:46 | 只看該作者
25#
發(fā)表于 2025-3-25 20:51:17 | 只看該作者
https://doi.org/10.1007/978-1-4615-5293-2a problem commonly known as archiving. Most of the currently available archiving algorithms are reviewed, and what is known about their convergence and approximation properties is summarized. The main scenario considered is the restricted case where the archive must be updated online as points are g
26#
發(fā)表于 2025-3-26 01:07:14 | 只看該作者
Fabio Taucer,Roberta Apostolskat algorithms that work on rather arbitrary functions, leading to Pareto-set sample estimates obtained in a single algorithm run, covering large portions of the Pareto-set. However, these solutions hardly reach the exact Pareto-set, which means that Pareto-optimality conditions do not hold on them. A
27#
發(fā)表于 2025-3-26 08:10:12 | 只看該作者
28#
發(fā)表于 2025-3-26 08:42:16 | 只看該作者
29#
發(fā)表于 2025-3-26 13:27:05 | 只看該作者
Robot Assisted Fracture Reduction from experimental data via its empirical counterpart, the empirical attainment function (EAF). However, computation of the EAF in more than two dimensions is a non-trivial task. In this article, the problem of computing the empirical attainment function is formalised, and upper and lower bounds on
30#
發(fā)表于 2025-3-26 18:10:01 | 只看該作者
Jaydev P. Desai,Gregory Dudek,Vijay Kumarween the hypervolume indicator of Y and the hypervolume indicator of Y ? {y}. In multi-objective metaheuristics, hypervolume contributions are computed in several selection and bounded-size archiving procedures..This paper presents new results on the (time) complexity of computing all hypervolume co
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