Ant Colony Optimization
Ant Colony Optimization
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DOI：
10.1007/978-3-642-01020-0_2
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发表时间：
2009-04
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影响因子：
--
通讯作者：
T. Stützle
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文献类型：
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作者：
T. Stützle
这本书是2009年1月在意大利特伦托举行的第三届国际学习与智能优化会议（LION 2009 III）经过彻底审核后的会议论文集。15篇修订全文、1篇扩展摘要和2篇海报会议经过仔细审查，并从86份提交的论文中选出纳入本书。论文涵盖了随机局部搜索方法和元启发式、约束和数学规划与元启发式的杂交、启发式搜索中应用的监督、无监督和强化学习、反应性搜索（在线自调整方法）、算法组合和离线调整方法、动态、随机和多目标问题的算法、离散和连续优化之间的接口、算法的实验分析与建模、理论基础、优化算法的并行化、基于记忆的优化、基于禁止的方法（禁忌搜索）、模因算法、进化算法、动态局部搜索、迭代局部搜索、可变邻域搜索和群体智能方法（蚁群优化、粒子群优化等）。
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Learning and Intelligent Optimization, LION 2009 III, held in Trento, Italy, in January 2009. The 15 revised full papers, one extended abstract and two poster sessions were carefully reviewed and selected from 86 submissions for inclusion in the book. The papers cover current issues of stochastic local search methods and meta-heuristics, hybridizations of constraint and mathematical programming with meta-heuristics, supervised, unsupervised and reinforcement learning applied to heuristic search, reactive search (online self-tuning methods), algorithm portfolios and off-line tuning methods, algorithms for dynamic, stochastic and multi-objective problems, interface (s) between discrete and continuous optimization, experimental analysis and modeling of algorithms, theoretical foundations, parallelization of optimization algorithms, memory-based optimization, prohibition-based methods (tabu search), memetic algorithms, evolutionary algorithms, dynamic local search, iterated local search, variable neighborhood search and swarm intelligence methods (ant colony optimization, particle swarm optimization etc.).