Small-world optimization based QoS multicast routing scheme with ABC supported

Wang, Xingwei; Huang, Min

doi:10.1109/ccdc.2009.5192949

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…Inspired by the mechanism of the small-world phenomenon in Milgram’s experiment, Du et al 1 presented the first new function optimization algorithm, known as the small-world algorithm (SWA) which consisted of a random long-range search operator and a local shortcut search operator. Wang et al 7 used the simple small-world algorithm (SSWA) to find a quality of service unicast path with the Pareto optimum under the Nash equilibrium condition with both the network provider utility and the user utility achieved or approached. A large number of simulation results have shown that the optimization performance of the SSWA is better than that of genetic algorithm (GA)-based approaches in terms of factors such as the diversity, convergence and search capability.…”

Section: Introductionmentioning

confidence: 99%

A novel small-world algorithm incorporating chaos optimization and its application to robot path planning

Yuan

Wang

et al. 2012

Proceedings of the Institution of Mechanical Engineers, Part I:

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By making use of the characteristics of ergodicity, randomicity and regularity of chaotic variables and information entropy, a novel chaotic small-world algorithm is presented to improve the optimization performance of the simple small-world algorithm. Compared with the corresponding simple small-world algorithm and the modified genetic algorithm approach, the optimization results of selected complex functions indicate that the proposed chaotic small-world algorithm is characterized by a strong search capability and a quick convergence speed. A study of parameter performance of the chaotic small-world algorithm aids in further improvement of its optimization capability. Additionally, the chaotic small-world algorithm is applied to mobile robot path planning, and the global path is optimized by the chaotic small-world algorithm based on a MAKLINK graph. Finally, experimental results verify the validity of the chaotic smallworld algorithm for robot path planning.

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Section: Introductionmentioning

confidence: 99%