Modified multi-verse optimiser used for global optimisation

IF 0.8 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Swarm Intelligence Research Pub Date : 1900-01-01 DOI:10.1504/IJSI.2021.10036209

D. K. Mishra, V. Shinde

引用次数: 1

Abstract

: In this paper, modified version of multi-verse optimiser (MVO) was suggested and tested on numerical optimisation problems. MVO is an innovative optimisation approach which stimulated from the concepts of cosmology; they are named as white hole, black hole and wormhole. Mathematical modelling of this concept has been carried out to acquire exploitation, exploration and local search. Modification in MVO has been made by introducing concept of dynamic variation in population size (universe). Modified multi-verse optimiser (MMVO) was tested on 16 benchmark functions having different complexity. Statistical comparisons of other algorithms outcomes is depicted that MMVO performs better than other algorithms.

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修改了用于全局优化的多宇宙优化器

本文提出了修正版的多重宇宙优化器(multi-verse optimizer, MVO)，并对数值优化问题进行了测试。MVO是一种创新的优化方法，它激发了宇宙学的概念;它们被命名为白洞、黑洞和虫洞。对这一概念进行了数学建模，以获取开采、勘探和局部搜索。引入种群大小(宇宙)动态变化的概念，对MVO进行了修正。在16个不同复杂度的基准函数上测试了改进的多重宇宙优化器(MMVO)。对其他算法结果的统计比较表明，MMVO的性能优于其他算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Swarm Intelligence Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

2.50

自引率

0.00%

发文量

期刊介绍： The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.