鎶ュ憡棰樼洰錛歋warm Intelligence for Dynamic Optimization Problems
銆€銆€鎶ュ憡鏃墮棿錛?鏈?0鏃ヤ笂鍗?:30
銆€銆€鎶ュ憡鍦扮偣錛氫話鍗楀崡妤?07-2
銆€銆€鎶ュ憡綆€浠嬶細(xì)Swarm intelligence (SI) in biology represents the property that the collective behavior of a swarm of agents that interact locally with their environment causes coherent functional global patterns to emerge. SI algorithms are optimization algorithms inspired from the SI phenomena in biology, such as ant foraging and bird flocking, and have been applied in different fields. Most SI algorithms have been developed to address stationary problems. However, many real-world problems are dynamic optimization problems (DOPs) that are subject to changes over time. DOPs have attracted a growing interest from the SI community in recent years due to the importance in the real-world applications of SI algorithms. This talk will first briefly introduce the concepts of SI and DOPs, then review the enhancement strategies integrated into SI algorithms to address DOPs, and describe several detailed case studies on SI methods for DOPs. Finally, some conclusions will be made and the future work on SI for DOPs will be briefly discussed.
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鏈虹數(shù)瀛﹂櫌
2018騫?鏈?5鏃?/p>
