標(biāo)題: Titlebook: Metaheuristics for Dynamic Optimization; Enrique Alba,Amir Nakib,Patrick Siarry Book 2013 Springer-Verlag Berlin Heidelberg 2013 Computati [打印本頁(yè)] 作者: 強(qiáng)烈的愿望 時(shí)間: 2025-3-21 18:39
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作者: 無(wú)可非議 時(shí)間: 2025-3-21 21:22
Metaheuristics for Dynamic Optimization978-3-642-30665-5Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: 輕浮思想 時(shí)間: 2025-3-22 02:15
https://doi.org/10.1007/978-3-642-30665-5Computational Intelligence; Dynamic Optimization; Metaheuristics作者: Modicum 時(shí)間: 2025-3-22 06:33
Enrique Alba,Amir Nakib,Patrick SiarryRecent research on Metaheuristics for Dynamic Optimization.Carefully edited book.Written by leading experts in the field作者: Suggestions 時(shí)間: 2025-3-22 09:11
Studies in Computational Intelligencehttp://image.papertrans.cn/m/image/631369.jpg作者: concert 時(shí)間: 2025-3-22 16:07 作者: Formidable 時(shí)間: 2025-3-22 18:33 作者: 準(zhǔn)則 時(shí)間: 2025-3-22 21:18
Dynamic Multi-Objective Optimization Using PSO,Swarm optimization (DVEPSO) algorithm when solving DMOOP. Furthermore, the performance of DVEPSO is compared against the performance of three other state-of-the-art dynamic multi-objective optimization algorithms.作者: 破裂 時(shí)間: 2025-3-23 02:47
Ant Colony Based Algorithms for Dynamic Optimization Problems, even a partition of vertices. In this chapter we present a general overview of the more relevant works regarding the application of ant colony based algorithms for dynamic optimization problems. We will also highlight the mechanisms used in different implementations found in the literature, and thu作者: 極大的痛苦 時(shí)間: 2025-3-23 09:36
Artificial Immune System for Solving Dynamic Constrained Optimization Problems, here to solve DCOPs. Besides, the performance of our proposed DCTC is compared with respect to those of two approaches which have been used to solve dynamic constrained optimization problems (RIGA and dRepairRIGA). Some statistical analysis is performed in order to get some insights into the effect作者: 新字 時(shí)間: 2025-3-23 10:10
Metaheuristics for Dynamic Vehicle Routing,ices, etc.). In this chapter, the DVRP is examined, and a survey on solving methods such as population-based metaheuristics and trajectory-based metaheuristics is exposed. Dynamic performances measures of different metaheuristics are assessed using dedicated indicators for the dynamic environment.作者: 頌揚(yáng)國(guó)家 時(shí)間: 2025-3-23 17:05
From the TSP to the Dynamic VRP: An Application of Neural Networks in Population Based Metaheuristimultaneously minimize the route lengths and the customer waiting time. The experiments show that the approach outperforms the operations research heuristics that were already applied to the Kilby et al. benchmark of 22 problems with up to 385 customers, which is one of the very few benchmark sets co作者: BRAWL 時(shí)間: 2025-3-23 19:51
Dynamic Time-Linkage Evolutionary Optimization: Definitions and Potential Solutions,ork to help characterising DOPs and DTPs. Second, we will identify a new and challenging class of DTPs where it might not be possible to solve the problems using traditional methods. Third, an approach to solve this class of problems under certain circumstances will be suggested and experiments to v作者: puzzle 時(shí)間: 2025-3-24 01:16
Book 2013lso, neural network solutions are considered in this book. .Both, theory and practice have been addressed in the chapters of the book. Mathematical background and methodological tools in solving this new class of problems and applications are included. From the applications point of view, not just a作者: 翻布尋找 時(shí)間: 2025-3-24 05:53 作者: 通知 時(shí)間: 2025-3-24 08:05 作者: antidote 時(shí)間: 2025-3-24 12:10 作者: nascent 時(shí)間: 2025-3-24 15:56
Victoria S. Aragón,Susana C. Esquivel,Carlos A. Coellog of transport in quantum wires. Furthermore, the chaotic and the correlation aspects of the transport in quantum dot systems are described. The status of the e978-94-010-7287-8978-94-009-1760-6Series ISSN 0168-132X 作者: 圓錐 時(shí)間: 2025-3-24 21:33 作者: 改進(jìn) 時(shí)間: 2025-3-25 00:28
Pedro C. Pinto,Thomas A. Runkler,Jo?o M. C. Sousas exist il1dependently of human observations and, if so, is it possible for man to understand correctly their behavior? By and large, it can be said that the Co978-94-010-7330-1978-94-009-1862-7Series ISSN 0168-1222 Series E-ISSN 2365-6425 作者: 神化怪物 時(shí)間: 2025-3-25 05:01 作者: HAIRY 時(shí)間: 2025-3-25 11:32 作者: 帶來(lái)墨水 時(shí)間: 2025-3-25 13:12 作者: ALOFT 時(shí)間: 2025-3-25 17:21
Amir Nakib,Patrick Siarryliver quantitatively, the relationship between the scatterer distribution and the PDF of echo envelopes of inhomogeneous scattering media using computer simulations was examined. Based on these simulations, the analysis parameters in the simulated fibrotic tissue were successfully used to characteri作者: EXTOL 時(shí)間: 2025-3-25 22:13
Briseida Sarasola,Enrique Albaon-linear methods for classification offer promise as a means of more-reliably distinguishing cancerous lesions from non-cancerous tissue in the prostate. Such advanced methods have produced areas under ROC curves exceeding 0.84 compared to an area of 0.64 for conventional assessments of the same lo作者: 憎惡 時(shí)間: 2025-3-26 02:42 作者: 鑒賞家 時(shí)間: 2025-3-26 06:05 作者: Latency 時(shí)間: 2025-3-26 09:49
Kalyanmoy Deb participating in violence and witnessing one’s home being burnt. Just under four-fifths (78%) of those who had experienced at least one traumatic event had one or more symptoms of PTSD. This syndrome was found to be related to feelings of powerlessness, anxiety and depression and fair or poor self-作者: OREX 時(shí)間: 2025-3-26 13:54
Mathys C. du Plessis,Andries P. Engelbrecht with a very large backlog in socio-economic development. There is evidence of breakdown in the society’s social cohesion. Popular expectations of future quality of life indicate that the euphoria following on the first democratic elections has been replaced by a sense of realism among all sectors o作者: A保存的 時(shí)間: 2025-3-26 19:26 作者: 無(wú)政府主義者 時(shí)間: 2025-3-27 00:38 作者: Angiogenesis 時(shí)間: 2025-3-27 03:51
Amir Hajjam,Jean-Charles Créput,Abderrafi?a Koukam2] is prevalent. We emphasize that in order to obtain a reasonable answer it is not sufficient to consider non-interacting electrons, a Fermi liquid or even a Luttinger liquid with short range interactions. An analysis based on an electric circuit model gives an answer which conserves the total char作者: 思想上升 時(shí)間: 2025-3-27 08:18
d. In Section 3, estimates are established for integrals of the potential type, which are later used in Section 4 to establish the relations between the classes . .(.) and the classes ..(.) and .(.). Section 4 studies the classes . .(.). In Section 5 we give the general theorem about differentiabili作者: MEET 時(shí)間: 2025-3-27 09:34 作者: MULTI 時(shí)間: 2025-3-27 15:51
Performance Analysis of Dynamic Optimization Algorithms,y their use by the community. In this chapter, we cite many tested problems (we focused only on the continuous case), and we only present the most used: the moving peaks benchmark?, and the last proposed: the generalized approach to construct benchmark problems for dynamic optimization (also called benchmark GDBG).作者: 積習(xí)已深 時(shí)間: 2025-3-27 18:08
Dynamic Function Optimization: The Moving Peaks Benchmark, problem. The majority of these approaches are nature-inspired. The results of the best-performing solutions based on the MP benchmark are directly compared and discussed. In the concluding remarks, the main characteristics of good approaches for dynamic optimization are summarised.作者: echnic 時(shí)間: 2025-3-28 01:34
SRCS: A Technique for Comparing Multiple Algorithms under Several Factors in Dynamic Optimization Po detect algorithms’ behavioral patterns. However, as every form of compression, it implies the loss of part of the information. The pros and cons of this technique are explained, with a special emphasis on some statistical issues that commonly arise when dealing with random-nature algorithms.作者: 治愈 時(shí)間: 2025-3-28 04:05
1860-949X ated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are作者: 喪失 時(shí)間: 2025-3-28 10:09
Dynamic Combinatorial Optimization Problems: A Fitness Landscape Analysis,taphor to review previous work on evolutionary dynamic combinatorial optimization. This review highlights some of the properties unique to dynamic combinatorial optimization problems and paves the way for future research related to these important issues.作者: 粗語(yǔ) 時(shí)間: 2025-3-28 12:44
Elastic Registration of Brain Cine-MRI Sequences Using MLSDO Dynamic Optimization Algorithm, algorithm based on multiple local searches, called MLSDO, is used to accomplish this task. The obtained results are compared to those of several well-known static optimization algorithms. This comparison shows the efficiency of MLSDO, and the relevance of using a dynamic optimization algorithm to solve this kind of problems.作者: Nibble 時(shí)間: 2025-3-28 14:37 作者: 河流 時(shí)間: 2025-3-28 19:27 作者: 沉思的魚(yú) 時(shí)間: 2025-3-29 00:08
Insect Swarm Algorithms for Dynamic MAX-SAT Problems,d wasp swarm optimization algorithms, which are based in the real life behavior of ants and wasps, respectively. The algorithms are applied to several sets of static and dynamic MAX-SAT instances and are shown to outperform the greedy hill climbing and simulated annealing algorithms used as benchmarks.作者: 貪心 時(shí)間: 2025-3-29 05:05
Performance Analysis of Dynamic Optimization Algorithms, approaches developed to address these problems. The goal of this chapter is to present the different tools and benchmarks to evaluate the performances of the proposed algorithms. Indeed, testing and comparing the performances of a new algorithm to the different competing algorithms is an important 作者: comely 時(shí)間: 2025-3-29 10:19 作者: 誘惑 時(shí)間: 2025-3-29 12:38
Dynamic Function Optimization: The Moving Peaks Benchmark,ete restart of the optimization algorithm may not be warranted. In those cases, it is meaningful to apply optimization algorithms that can accommodate change. In the recent past, many researchers have contributed algorithms suited for dynamic problems. To facilitate the comparison between different 作者: Ingredient 時(shí)間: 2025-3-29 16:06
SRCS: A Technique for Comparing Multiple Algorithms under Several Factors in Dynamic Optimization Pthe researcher usually tests many algorithms, with several parameters, under different problems. The situation is even more complex when dynamic optimization problems are considered, since additional dynamism-specific configurations should also be analyzed (e.g. severity, frequency and type of the c作者: 輕而薄 時(shí)間: 2025-3-29 23:26
Dynamic Combinatorial Optimization Problems: A Fitness Landscape Analysis,lems thanks to a variety of empirical studies as well as some theoretical results. In the field of evolutionary dynamic optimization very few studies exist to date that explicitly analyse the impact of these elements on the algorithm’s performance. In this chapter we utilise the fitness landscape me作者: Cpap155 時(shí)間: 2025-3-30 03:33 作者: arcane 時(shí)間: 2025-3-30 05:58 作者: 職業(yè) 時(shí)間: 2025-3-30 11:55
Dynamic Multi-Objective Optimization Using PSO,ve, but many goals that are in conflict with one another - improvement in one goal leads to deterioration of another. Therefore, when solving dynamic multi-objective optimization problem, an algorithm attempts to find the set of optimal solutions, referred to as the Pareto-optimal front. Each dynami作者: 收集 時(shí)間: 2025-3-30 15:47
Ant Colony Based Algorithms for Dynamic Optimization Problems, used and assessed techniques. Nevertheless, successful applications coming from other nature-inspired metaheuristics, e.g., ant algorithms, have also shown their applicability in dynamic optimization problems, but received a limited attention until now. Different from perturbative techniques, ant a作者: 減弱不好 時(shí)間: 2025-3-30 19:10
Elastic Registration of Brain Cine-MRI Sequences Using MLSDO Dynamic Optimization Algorithm, of a brain cine-MR imaging. In this method, an elastic registration process is applied to a 2D+t cine-MRI sequence of a region of interest (i.e. lamina terminalis). This registration process consists in optimizing an objective function that can be considered as dynamic. Thus, a dynamic optimization作者: Filibuster 時(shí)間: 2025-3-30 22:28
Artificial Immune System for Solving Dynamic Constrained Optimization Problems,roach is called Dynamic Constrained T-Cell (DCTC) and it is an adaptation of an existing algorithm, which was originally designed to solve static constrained problems. Here, this approach is extended to deal with problems which change over time and whose solutions are subject to constraints. Our pro作者: 打包 時(shí)間: 2025-3-31 03:02 作者: Organonitrile 時(shí)間: 2025-3-31 07:51
Low-Level Hybridization of Scatter Search and Particle Filter for Dynamic TSP Solving,F combines sequential estimation and combinatorial optimization methods to efficiently address dynamic optimization problems. SSPF obtains high quality solutions at each time step by taking advantage of the best solutions obtained in the previous ones. To demonstrate the performance of the proposed 作者: abstemious 時(shí)間: 2025-3-31 10:39 作者: Countermand 時(shí)間: 2025-3-31 15:36
Insect Swarm Algorithms for Dynamic MAX-SAT Problems,limited number of theoretical and real-world problems come as instances of SAT or MAX-SAT, many combinatorial problems can be encoded into them. This puts the study of MAX-SAT and the development of adequate algorithms to address it in an important position in the field of computer science. Among th作者: headway 時(shí)間: 2025-3-31 17:35
Dynamic Time-Linkage Evolutionary Optimization: Definitions and Potential Solutions,n influence how the problems might change in the future. Although DTPs are very common in real-world applications (e.g. online scheduling, online vehicle routing, and online optimal control problems), they have received very little attention from the evolutionary dynamic optimization (EDO) research 作者: Hemiparesis 時(shí)間: 2025-3-31 22:43
