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 publication and its significant other quantity, LNCS vol. 8794 and 8795 represent the complaints of the fifth overseas convention on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised complete papers provided have been rigorously reviewed and chosen from 198 submissions. The papers are prepared in 18 cohesive sections, three distinct periods and one aggressive consultation protecting all significant issues of swarm intelligence learn and improvement equivalent to novel swarm-based seek equipment; novel optimization set of rules; particle swarm optimization; ant colony optimization for vacationing salesman challenge; man made bee colony algorithms; man made immune procedure; evolutionary algorithms; neural networks and fuzzy tools; hybrid tools; multi-objective optimization; multi-agent platforms; evolutionary clustering algorithms; class tools; GPU-based tools; scheduling and direction making plans; instant sensor networks; energy procedure optimization; swarm intelligence in snapshot and video processing; functions of swarm intelligence to administration difficulties; swarm intelligence for real-world application.

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

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Besides that, ACO is suitable for discrete problem like traveling salesperson problem (TSP), and it is hard to convergence to the global optimal solution when the number of cities is too great. The simulated annealing (SA) makes use of the metropolis acceptance criteria to help to jump out of the local extremum regions, but it includes too many repetitive iterations and this requirement is difficult to be met in the practical applications. Therefore, SA is just a heuristic random process based on Monte Carlo method.

We observe that the velocity curve of our model is very close to the velocity curve representing real data. It is very important to note that the personality’s variation affects the flow characteristics [30]. In fact, the flow characteristics include pedestrian’s velocity and pedestrian’s flow rates. For this purpose, we must take into consideration not only the velocity but also the flow rates. We repeated the same previous experiment, but this time we measured the flow of pedestrian traffic rather than the average velocity.

If its evaluation function value does not be improved yet, the individual will carry out self-learning. It means that the individual will get its dual individual via dual operation. What is more, the best individual in each niche population will be fixed with the program process goes, because every niche population will exchange its best individual with other niche populations. So the internal benchmarking in each population, namely, the learning object of the staff inside each population will be replaced by other internal benchmarking.

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