作者: Expressly 時間: 2025-3-21 22:33
Neutral but a Winner! How Neutrality Helps Multiobjective Local Search Algorithmssteps from the perspective of neutrality in multi-objective landscapes, propose new strategies that take into account neutrality, and show that exploiting neutrality allows to improve the performance of dominance-based local search methods on bi-objective permutation flowshop scheduling problems.作者: 千篇一律 時間: 2025-3-22 01:03 作者: 音樂會 時間: 2025-3-22 05:21 作者: Dorsal 時間: 2025-3-22 09:42 作者: 高爾夫 時間: 2025-3-22 14:42 作者: 高爾夫 時間: 2025-3-22 20:30 作者: propose 時間: 2025-3-22 21:32 作者: 不妥協(xié) 時間: 2025-3-23 04:13 作者: heckle 時間: 2025-3-23 05:42 作者: inhibit 時間: 2025-3-23 11:19
António Gaspar-Cunha,Carlos Henggeler Antunes,Carl作者: 隱士 時間: 2025-3-23 16:38 作者: 誓言 時間: 2025-3-23 20:13 作者: Rustproof 時間: 2025-3-24 01:08 作者: separate 時間: 2025-3-24 06:08 作者: Free-Radical 時間: 2025-3-24 08:45 作者: Acupressure 時間: 2025-3-24 10:46 作者: 過份 時間: 2025-3-24 17:56 作者: alliance 時間: 2025-3-24 20:32 作者: 腐蝕 時間: 2025-3-24 23:28
978-3-319-15933-1Springer International Publishing Switzerland 2015作者: Costume 時間: 2025-3-25 03:48
Evolutionary Multi-Criterion Optimization978-3-319-15934-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 某人 時間: 2025-3-25 10:30 作者: COM 時間: 2025-3-25 11:39
Arie Arnon,Warren Young,Karine van der BeekASs). Prescriptive approaches to manually preload these systems with a limited set of strategies/solutions before deployment often result in brittle, rigid designs that are unable to scale and cope with environmental uncertainty. Alternatively, a more scalable and adaptable approach is to embed a se作者: Mumble 時間: 2025-3-25 17:57
https://doi.org/10.1007/978-3-319-50702-6erformance of multi-objective dominance-based local search methods. We discuss neutrality in single-objective optimization and fitness assignment in multi-objective algorithms to provide a general definition for neutrality applicable to multi-objective landscapes. We also put forward a definition of作者: encomiast 時間: 2025-3-25 22:45
Stackelberg Duopoly Models Reconsidered,, or see DE as an algorithmic component that can be coupled with other algorithm components from the general evolutionary multiobjective optimization (EMO) literature. Contributions of the latter type have shown that DE components can greatly improve the performance of existing algorithms such as NS作者: Culmination 時間: 2025-3-26 00:58 作者: observatory 時間: 2025-3-26 06:31 作者: subordinate 時間: 2025-3-26 11:45 作者: 共同生活 時間: 2025-3-26 13:29 作者: 保留 時間: 2025-3-26 17:50 作者: Adrenaline 時間: 2025-3-27 00:15
https://doi.org/10.1007/978-3-662-63730-2ization. The performance of any multiobjective evolutionary algorithm (MOEA) is strongly related to the efficacy of its selection mechanism. The population convergence and diversity are two different but equally important goals that must be ensured by the selection mechanism. Despite the equal impor作者: 拖網 時間: 2025-3-27 02:59
Ralf Jaumann,Ulrich K?hler,Susanne Piethic programming problems. First, we investigate two scalarizing strategies that iteratively identify a high-quality solution for a sequence of sub-problems. Each sub-problem is based on a static or adaptive definition of weighted-sum aggregation coefficients, and is addressed by means of a state-of-t作者: Transfusion 時間: 2025-3-27 07:38 作者: 過分自信 時間: 2025-3-27 13:10
Practical Nursing Principles Afloats that are usually assumed to be given by a decision maker (DM) based on his/her preference. However, setting the reference point needs a priori knowledge that the DM sometimes does not have. In order to obtain favorable solutions without a priori knowledge, “knee points” can be used. Some algorithm作者: 用不完 時間: 2025-3-27 13:43 作者: 寬敞 時間: 2025-3-27 21:35 作者: 禁止 時間: 2025-3-27 22:09 作者: meditation 時間: 2025-3-28 03:38 作者: TRUST 時間: 2025-3-28 08:46 作者: Derogate 時間: 2025-3-28 10:54 作者: 強制令 時間: 2025-3-28 18:29 作者: 殺菌劑 時間: 2025-3-28 20:24 作者: sphincter 時間: 2025-3-28 23:19
Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmarks derived. It is shown which contributions were made to which phase of the MBMO process. A special attention is given to the proposal of a set of points for parallel evaluation within a batch. Proposals for four different MBMO algorithms are presented and compared to their sequential variants within作者: Enthralling 時間: 2025-3-29 06:42
Temporal Innovization: Evolution of Design Principles Using Multi-objective Optimizationsolutions lie on the Pareto-optimal front which is a lower-dimensional slice of the objective space. Together, the solutions may possess special properties that make them optimal over other feasible solutions. Innovization is the process of extracting such special properties (or design principles) f作者: Tartar 時間: 2025-3-29 08:14 作者: Truculent 時間: 2025-3-29 14:01
Using Hyper-Heuristic to Select Leader and Archiving Methods for Many-Objective Problemsed different leader and archiving methods to tackle the challenges caused by the increase in the number of objectives, however, selecting the most appropriate components for a given problem is not a trivial task. Moreover, the algorithm can take advantage by using a variety of methods in different p作者: 鄙視讀作 時間: 2025-3-29 18:30 作者: 思想上升 時間: 2025-3-29 21:29 作者: Gastric 時間: 2025-3-30 00:34
Experiments on Local Search for Bi-objective Unconstrained Binary Quadratic Programmingic programming problems. First, we investigate two scalarizing strategies that iteratively identify a high-quality solution for a sequence of sub-problems. Each sub-problem is based on a static or adaptive definition of weighted-sum aggregation coefficients, and is addressed by means of a state-of-t作者: 發(fā)出眩目光芒 時間: 2025-3-30 05:34 作者: 牌帶來 時間: 2025-3-30 08:41
A Knee-Based EMO Algorithm with an Efficient Method to Update Mobile Reference Pointss that are usually assumed to be given by a decision maker (DM) based on his/her preference. However, setting the reference point needs a priori knowledge that the DM sometimes does not have. In order to obtain favorable solutions without a priori knowledge, “knee points” can be used. Some algorithm作者: 廚師 時間: 2025-3-30 12:52 作者: 友好 時間: 2025-3-30 17:29 作者: Spinal-Fusion 時間: 2025-3-30 20:48 作者: 一個攪動不安 時間: 2025-3-31 02:05
Utility Theory: Axioms Versus ‘Paradoxes’l Evolution mutation strategy) that should be applied to each individual during a MOEA/D execution. We tested MOEA/D-HH in a well established set of 10 instances from the CEC 2009 MOEA Competition. MOEA/D-HH is compared with some important multi-objective optimization algorithms and the resultsobtained are promising.
