Results 11 to 20 of about 21,443 (267)
Ant colony optimization theory: A survey [PDF]
Theoretical Computer Science, 2005 Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an ...
Marco Dorigo, Christian Blum
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Test pattern optimization scheme based on Hybrid Ant Colony Optimization [PDF]
Scientific ReportsThe trend toward device miniaturization has made digital circuit testing both essential and increasingly complex. To achieve complete fault coverage, a large number of test patterns are applied, which leads to increased switching activity due to larger ...
S. Asha Pon, V. Jeyalakshmi
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Ant colony optimization: A bibliometric review
Physics of Life ReviewsThis paper is a follow-up of one of the most-cited articles published in the first 20 years of the existence of Physics of Life Reviews. The specific topic is "ant colony optimization", which is a metaheuristic for solving challenging optimization problems.
Christian Blum
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Ant colony optimization with immigrants schemes in dynamic environments [PDF]
, 2010 This is the post-print version of this article. The official published version can be accessed from the link below - Copyright @ 2010 Springer-VerlagIn recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs ...
Yang, S +5 more
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Path planning of multiple UAVs using MMACO and DE algorithm in dynamic environment
Measurement + Control, 2023 Cooperative path planning of multiple unmanned aerial vehicles is a complex task. The collision avoidance and coordination between multiple unmanned aerial vehicles is a global optimal issue.
Zain Anwar Ali, Han Zhangang, Di Zhengru
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Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2009 Ant Colony Optimization (ACO) is a stochastic local search method that has been inspired by the pheromone trail laying and following behavior of some ant species [1]. Artificial ants in ACO essentially are randomized construction procedures that generate solutions based on (artificial) pheromone trails and heuristic information that are associated to ...
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Service Composition and Optimization Method Based on Improved Ant Colony Optimization Algorithm [PDF]
Jisuanji gongcheng, 2018 Aiming at the shortcomings of traditional ant colony algorithm,such as long initial pheromone accumulation time and easy to fall into local optimum,an improved ant colony system based cloud service composition algorithm is proposed under the condition of
SHEN Jiquan,LUO Changwei,HOU Zhanwei,LIU Zhizhong
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Single-Colony Adaptive Heterogeneous Ant Colony Algorithm for Mobile Robot Path Planning [PDF]
Jisuanji kexue yu tansuo, 2022 Aiming at the existent problems of complex structure, slow optimization rate and inadequate adaptability of multi-colony ant colony algorithm, a single colony adaptive heterogeneous ant colony algorithm is proposed to solve mobile robot path planning ...
ZHANG Songcan, SUN Lifan, SI Yanna, PU Jiexin
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Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, 2010 Swarm intelligence is a relatively novel approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful one is the ant colony optimization.
Benlian Xu, Jihong Zhu, Qinlan Che
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