کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4962840 1446756 2017 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Regular PaperTermite spatial correlation based particle swarm optimization for unconstrained optimization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Regular PaperTermite spatial correlation based particle swarm optimization for unconstrained optimization
چکیده انگلیسی

In last few years, swarm intelligence has become the mainstay in the field of continuous optimization with many researchers developing algorithms simulating swarm behavior for the purpose of numerical optimization. This work proposes a new Termite Spatial Correlation based Particle Swarm Optimization (TSC-PSO) algorithm inspired by the movement strategy shown within Termites (Cornitermes cumulans). TSC-PSO modifies the velocity equation in the original PSO algorithm by replicating the step correlation based termite motion mechanism that exhibits individually in nature and works with decentralized control to collectively perform the overall task. Further, the algorithm incorporates the mutation strategy within it to make it suitable to avoid stagnation conditions while performing optimization in complex search spaces. For deriving its utility various benchmark functions of different geometric properties have been used. Experiments clearly demonstrate the success of the proposed algorithm in different benchmark conditions against various state-of-the-art optimization algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Swarm and Evolutionary Computation - Volume 33, April 2017, Pages 93-107
نویسندگان
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