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Titlebook: Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heur; International Worksh Thomas Stützle,M

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書(shū)目名稱Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heur
副標(biāo)題International Worksh
編輯Thomas Stützle,Mauro Birattari,Holger H. Hoos
視頻videohttp://file.papertrans.cn/311/310968/310968.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heur; International Worksh Thomas Stützle,M
描述Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise
出版日期Conference proceedings 2009
關(guān)鍵詞Scheduling; algorithm performance; algorithms; ant colony; autonomous systems; combinatorial optimization
版次1
doihttps://doi.org/10.1007/978-3-642-03751-1
isbn_softcover978-3-642-03750-4
isbn_ebook978-3-642-03751-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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https://doi.org/10.1007/978-981-19-7485-4mization. We further explore run time distributions and describe a new tool to compare two algorithms based on stochastic local search. For the case where the running times of both algorithms fit exponential distributions, we derive a closed form index that gives the probability that one of them fin
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nt to grasp the relevant features. In this paper we present and discuss a set of techniques for the visualization of search landscapes aimed at supporting the researcher’s intuition on the behavior of a Stochastic Local Search algorithm applied to a combinatorial optimization problem..We discuss sca
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The Energetics of Mangrove Forestsques are applied to analyse the performance of two different metaheuristics for the team orienteering problem. Furthermore, the parameter setting problem is discussed and the parameter “sensitivity” is analysed.
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Building an Urban Energy Center,ion performed. A formalization in this sense is proposed here: A method for studying this aspect regardless the type of approach used is defined and tested. The consequent measure of exploration is applied to MAX–MIN Ant System: The impact of the values of the parameters on the exploration is assess
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