Download Advances in Swarm Intelligence: 5th International by Ying Tan, Yuhui Shi, Carlos Coello Coello PDF

By Ying Tan, Yuhui Shi, Carlos Coello Coello

This ebook and its spouse quantity, LNCS vol. 8794 and 8795 represent the complaints of the fifth foreign convention on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised complete papers offered have been rigorously reviewed and chosen from 198 submissions. The papers are equipped in 18 cohesive sections, three particular classes and one aggressive consultation masking all significant themes of swarm intelligence examine and improvement similar to novel swarm-based seek equipment; novel optimization set of rules; particle swarm optimization; ant colony optimization for vacationing salesman challenge; synthetic bee colony algorithms; man made immune method; evolutionary algorithms; neural networks and fuzzy equipment; hybrid equipment; multi-objective optimization; multi-agent platforms; evolutionary clustering algorithms; type equipment; GPU-based equipment; scheduling and course making plans; instant sensor networks; strength process optimization; swarm intelligence in photograph and video processing; functions of swarm intelligence to administration difficulties; swarm intelligence for real-world application.

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Extra resources for Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I

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Creating crowd variation with the ocean personality model. , Mller, J. ) AAMAS (3), pp. 1217–1220. IFAAMAS (2008) 2. : The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics. PLoS ONE 5(4), e10047+ (2010) 3. : Towards a cognitive model of crowd behavior based on social comparison theory. In: AAAI, pp. 731–737 (2007) 4. : Multi-agent simulation model of pedestrians crowd based on psychological theories. In: 4th International Conference on Logistics, LOGISTIQUA (2011) 5.

Furthermore, they are all population convergence-oriented. Benchmarking [1] originally means that a surveyor's mark on a permanent object of predetermined position and elevation used as a reference point. As a kind of management idea and management method, benchmarking learning originated from enterprise management domain, and it means that some outstanding enterprise can be set as a standard, by which other companies can be measured or judged, and improved consequently. 2 The Benchmarking Learning Algorithm (BLA) Benchmarking learning, in short, is to find the best case and learn something from it via imitate, others will improve themselves and even beyond the opponent.

The global optimal solution) 1 2 np i E ⅰ ⅱ ⅲ i (d) evaluate fE = (  fi ) np (e) for i=1:np, do . if f i j does not be improved then, Pi j will conduct internal benchmarking learning . if f i j does not be improved yet then, Pi j will carry out self-learning (f) if f does not be improved or the best individual in E does not be replaced do Pi will exchange its best individual with other niche populations (Namely,   ⅰ ⅱ ⅲ , , E each niche populations set a new external benchmarking) (3) Output the global optimal solution 3 Main Features The main features and advantages of BLA, which are different from and superior to other optimization methods, were described, analyzed and given as below.

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