Modified differential evolution algorithm for solving minimum spanning tree

被引：4

作者：

Jain, Sanjay ^{[1
]}

Kumar, Sandeep ^{[1
]}

Sharma, Vivek Kumar ^{[2
]}

Poonia, Ramesh C. ^{[3
]}

Lamba, Narendra Pal ^{[4
]}

机构：

[1] Amity Univ Jaipur, Dept Comp Sci & Engn, Jaipur 302002, Rajasthan, India

[2] Jagannath Univ, Dept Engn & Technol, Jaipur 303901, Rajasthan, India

[3] Norwegian Univ Sci & Technol, Fac Informat Technol & Elect Engn, Dept ICT & Nat Sci, Cyber Phys Syst Lab, Alesund, Norway

[4] Amity Univ Jaipur, Dept Chem, Jaipur 302002, Rajasthan, India

来源：

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES | 2020年 / 41卷 / 02期

关键词：

Evolutionary intelligence; Optimization; Path planning; Nature inspired algorithm;

D O I：

10.1080/02522667.2020.1733195

中图分类号：

G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];

学科分类号：

1205 ; 120501 ;

摘要：

Differential evolution (DE) is a stochastic approach based on the concept of natural evolution. It is very simple and robust evolutionary algorithm. DE has three simple steps and it is easy to implement. It is a popular meta-heuristics that efficiently solved various complex optimization problems. This paper addressed the minimum spanning tree problem. Here a new variant of DE with new scaling factor inspired by peregrine preying pattern. In addition to new scaling factor it make use of global best solution for updating current solution. Results shows that modified DE performs significantly better than other competitive algorithms for considered minimum spanning tree.

引用

页码：633 / 639

页数：7

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