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Titlebook: Advances in Swarm Intelligence; 5th International Co Ying Tan,Yuhui Shi,Carlos A. Coello Coello Conference proceedings 2014 Springer Intern

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发表于 2025-3-21 19:41:25 | 显示全部楼层 |阅读模式
期刊全称Advances in Swarm Intelligence
期刊简称5th International Co
影响因子2023Ying Tan,Yuhui Shi,Carlos A. Coello Coello
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Swarm Intelligence; 5th International Co Ying Tan,Yuhui Shi,Carlos A. Coello Coello Conference proceedings 2014 Springer Intern
影响因子This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.
Pindex Conference proceedings 2014
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发表于 2025-3-21 20:55:26 | 显示全部楼层
0302-9743 duling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.978-3-319-11856-7978-3-319-11857-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
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A Unique Search Model for Optimizationight of imitation and learning, all the individuals within population were able to approach to the high yielding regions in the solution space, and seek out the optimal solutions quickly. Secondly, the premature convergence problem got completely overcame through new optimal solution policy. Finally
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Improve the 3-flip Neighborhood Local Search by Random Flat Move for the Set Covering Problemmost challenging crew scheduling instances from Italy railways. We introduce a method to further improve the effectiveness of 3FNLS by incorporating random flat move to its search process. Empirical studies show that this can obviously improve the solution qualities of 3FNLS on the benchmark instanc
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Abnormal
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A Unified Matrix-Based Stochastic Optimization Algorithm. This paper does not focus on any subbranch, but on the metaheuristics research from a unified view. The population of decision vectors is looked on as an abstract matrix and three novel basic solution generation operations, E[p(i,j)], E[p(c·i)] and E[i, p(c·i+j)], are proposed in this paper. They
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