標(biāo)題: Titlebook: Advances in Stochastic and Deterministic Global Optimization; Panos M. Pardalos,Anatoly Zhigljavsky,Julius ?ilin Book 2016 Springer Intern [打印本頁(yè)] 作者: Hypothesis 時(shí)間: 2025-3-21 17:00
書目名稱Advances in Stochastic and Deterministic Global Optimization影響因子(影響力)
書目名稱Advances in Stochastic and Deterministic Global Optimization影響因子(影響力)學(xué)科排名
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書目名稱Advances in Stochastic and Deterministic Global Optimization網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Advances in Stochastic and Deterministic Global Optimization被引頻次
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書目名稱Advances in Stochastic and Deterministic Global Optimization讀者反饋
書目名稱Advances in Stochastic and Deterministic Global Optimization讀者反饋學(xué)科排名
作者: 催眠 時(shí)間: 2025-3-21 21:54
https://doi.org/10.1007/978-3-663-19701-0ple can have a great impact on the overall effectiveness of the optimization. In this study, we demonstrate how various sampling techniques affect the results of applying different optimization algorithms to a set of benchmark problems. Additionally, some recommendations on usage of sampling methods are provided.作者: 疲憊的老馬 時(shí)間: 2025-3-22 04:04
Survey of Piecewise Convex Maximization and PCMP over Spherical Setscult nonconvex optimization problem. We also review how the line search paradigm leads to a radius search paradigm, in the sense that sphere separation which seems to us more appropriate than the affine separation. Some simple, but illustrative, examples showing the issues in searching for a global solution are given.作者: 調(diào)整校對(duì) 時(shí)間: 2025-3-22 06:46 作者: forebear 時(shí)間: 2025-3-22 08:47
A Multicriteria Generalization of Bayesian Global Optimizationhemes by a factor of .∕log.. It shows that this measure, at least for a small number of objective functions, is as fast as other simpler measures of multicriteria expected improvement that were considered in recent years.作者: 惡意 時(shí)間: 2025-3-22 15:50 作者: propose 時(shí)間: 2025-3-22 19:15
Book 2016is book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, a作者: voluble 時(shí)間: 2025-3-22 22:03 作者: Enrage 時(shí)間: 2025-3-23 02:46
H. Suzuki,K. Kase,K. Kato,F. Kimuraigent data analysis including data visualization methods. It can assist researchers to handle large amounts of multidimensional data when executing resource-expensive and time-consuming data mining tasks by considerably reducing the information load. The application of DAMIS is illustrated by the visual analysis of medical streaming data.作者: 容易做 時(shí)間: 2025-3-23 09:36 作者: 事情 時(shí)間: 2025-3-23 11:34 作者: MELON 時(shí)間: 2025-3-23 15:54 作者: STING 時(shí)間: 2025-3-23 21:26
Vijay Srinivasan,Michael A. O’Connorh it does not preserve the true relationships. However, if the input dissimilarities are unreliable, too difficult to measure or simply unavailable, a non-metric MDS is the appropriate algorithm. In?this paper, we give overview of both metric and non-metric MDS methods and their application to genomic data analyses.作者: Intuitive 時(shí)間: 2025-3-24 00:30 作者: 打折 時(shí)間: 2025-3-24 03:35
Multidimensional Scaling for Genomic Datah it does not preserve the true relationships. However, if the input dissimilarities are unreliable, too difficult to measure or simply unavailable, a non-metric MDS is the appropriate algorithm. In?this paper, we give overview of both metric and non-metric MDS methods and their application to genomic data analyses.作者: 諂媚于性 時(shí)間: 2025-3-24 09:01 作者: commodity 時(shí)間: 2025-3-24 13:53
Assessing Basin Identification Methods for Locating Multiple Optimahem as components. In this work, we compare two approaches on their own, namely topographical selection and nearest-better clustering, regarding their ability to identify the distinct attraction basins of multimodal functions. We show that both have different strengths and weaknesses, as their behavior is very dependent on the problem instance.作者: Proponent 時(shí)間: 2025-3-24 14:52
On Sampling Methods for Costly Multi-Objective Black-Box Optimizationple can have a great impact on the overall effectiveness of the optimization. In this study, we demonstrate how various sampling techniques affect the results of applying different optimization algorithms to a set of benchmark problems. Additionally, some recommendations on usage of sampling methods are provided.作者: 全神貫注于 時(shí)間: 2025-3-24 21:42 作者: Enliven 時(shí)間: 2025-3-24 23:54 作者: Geyser 時(shí)間: 2025-3-25 04:00 作者: 怕失去錢 時(shí)間: 2025-3-25 10:01
https://doi.org/10.1007/978-3-663-19701-0 nonlinear bi-objective optimization problem. A?heuristic algorithm is proposed which obtains a good approximation of the Pareto front when the new facilities have to be selected from a finite set of candidates.作者: 鄙視讀作 時(shí)間: 2025-3-25 12:04 作者: Cerebrovascular 時(shí)間: 2025-3-25 16:09
Combining Interval and Probabilistic Uncertainty: What Is Computable?thms for taking uncertainty into account..Before we concentrate our efforts on designing such algorithms, it is important to make sure that such an algorithm is possible in the first place, i.e., that the corresponding problem is algorithmically computable. In this paper, we analyze the computabilit作者: HARP 時(shí)間: 2025-3-25 20:58 作者: 適宜 時(shí)間: 2025-3-26 02:44 作者: debunk 時(shí)間: 2025-3-26 07:55
Understanding the Impact of Constraints: A Rank Based Fitness Function for Evolutionary Methodseparate objective. The results presented show that the fitness function provides the desired selection pressure and, when combined with the multi-objective plant propagation algorithm, is able to find good designs that achieve the desired constraint simultaneously.作者: Arctic 時(shí)間: 2025-3-26 08:42
Advances in Stochastic and Deterministic Global Optimization作者: 固執(zhí)點(diǎn)好 時(shí)間: 2025-3-26 16:39
Book 2016objective function, the development and implementation of efficient algorithms for global optimization with single and multiple objectives, and application of algorithms for solving real-world practical problems..作者: fulmination 時(shí)間: 2025-3-26 17:18
Christian Liebchen,Rolf H. M?hringthms for taking uncertainty into account..Before we concentrate our efforts on designing such algorithms, it is important to make sure that such an algorithm is possible in the first place, i.e., that the corresponding problem is algorithmically computable. In this paper, we analyze the computabilit作者: gruelling 時(shí)間: 2025-3-26 23:43
https://doi.org/10.1007/978-94-009-1529-9for the master problem. Each column corresponds to one possible tree of actions for one ship giving its schedule loading/unloading quantities for all demand scenarios. Computational results are given showing that medium sized problems can be solved successfully.作者: Spangle 時(shí)間: 2025-3-27 03:13
Jorge Freire Sousa,Riccardo Rossirk we are undertaking using interval methods.In our work a verified solver that constructs upper and lower bounds on the dynamic variables of initial value problem (IVP) for ODEs is used in a dynamic global optimization method (sequential approach). Particular attention is paid to the reduction of t作者: 耐寒 時(shí)間: 2025-3-27 07:35 作者: 鋼筆記下懲罰 時(shí)間: 2025-3-27 11:39
Christian Liebchen,Rolf H. M?hringWe consider the intrinsic difficulty of global optimization in high dimensional Euclidean space. We adopt an asymptotic analysis, and give a lower bound on the number of function evaluations required to obtain a given error tolerance. This lower bound complements upper bounds provided by recently proposed algorithms.作者: 凹室 時(shí)間: 2025-3-27 16:55 作者: Torrid 時(shí)間: 2025-3-27 17:46 作者: Mendicant 時(shí)間: 2025-3-27 23:00
Mixed-Fleet Ferry Routing and Scheduling, .. Such piecewise convex functions closely approximate nonconvex functions, that seems to us as a natural extension of the piecewise affine approximation from convex analysis. Maximizing .(??) over a convex domain have been investigated during the last decade by carrying tools based mostly on line作者: Landlocked 時(shí)間: 2025-3-28 05:09 作者: browbeat 時(shí)間: 2025-3-28 06:38 作者: IRATE 時(shí)間: 2025-3-28 14:02 作者: Suggestions 時(shí)間: 2025-3-28 17:55 作者: PACT 時(shí)間: 2025-3-28 21:44 作者: capsaicin 時(shí)間: 2025-3-29 01:10 作者: hardheaded 時(shí)間: 2025-3-29 04:14 作者: 滋養(yǎng) 時(shí)間: 2025-3-29 08:25
Antonio Polimeni,Antonino Vitettanlinear least-squares global optimization problem. A one-parametric case study is examined to determine an unknown frequency of a signal. Univariate Lipschitz-based deterministic methods are used for solving such problems within a limited computational budget. It is shown that the usage of local inf作者: floaters 時(shí)間: 2025-3-29 14:27 作者: backdrop 時(shí)間: 2025-3-29 18:01 作者: Fissure 時(shí)間: 2025-3-29 21:31
https://doi.org/10.1007/978-3-663-19701-0ation of the market share captured by the new facilities and minimization of the lost market share of the old facilities caused by the entering of the new facilities in the market. The market share of each facility is estimated assuming that customers are served by the most attractive facility. A ne作者: 極少 時(shí)間: 2025-3-30 00:00
https://doi.org/10.1007/978-3-663-19701-0mization problems. Such problems are often solved using an algorithm in which a surrogate model approximates the true objective function and provides predicted objective values at a lower cost. As the surrogate model is based on evaluations of a small number of points, the quality of the initial sam作者: 線 時(shí)間: 2025-3-30 05:27 作者: 依法逮捕 時(shí)間: 2025-3-30 11:34 作者: foodstuff 時(shí)間: 2025-3-30 15:15 作者: 謙虛的人 時(shí)間: 2025-3-30 19:59 作者: 詩(shī)集 時(shí)間: 2025-3-30 22:52 作者: 彎曲道理 時(shí)間: 2025-3-31 04:30
Combining Interval and Probabilistic Uncertainty: What Is Computable?ntities. In these computations, it is important to take into account that measurement results are never absolutely exact, that there is always measurement uncertainty, because of which the measurement results are, in general, somewhat different from the actual (unknown) values of the corresponding q作者: flaggy 時(shí)間: 2025-3-31 07:38 作者: 刪減 時(shí)間: 2025-3-31 12:17
Assessing Basin Identification Methods for Locating Multiple Optima this task is obtaining topographical information about the objective function from a discrete sample of the search space and representing it in a graph structure. So far, different variants of this approach are usually assessed by evaluating the performance of a whole optimization algorithm using t作者: Hla461 時(shí)間: 2025-3-31 15:05
Cloud Computing Approach for Intelligent Visualization of Multidimensional Dataate visualization models based on the best practices and experience. A new Cloud computing-based data mining system DAMIS is introduced for the intelligent data analysis including data visualization methods. It can assist researchers to handle large amounts of multidimensional data when executing re作者: 核心 時(shí)間: 2025-3-31 19:05
Comparative Study of Different Penalty Functions and Algorithms in Survey Calibrationocess is an optimization procedure, for which a variety of penalty functions can be used. In this chapter, we consider three of the classical penalty functions that are implemented in many of the standard calibration software packages. We present two algorithms used by many of these software package
