Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems

2021 ◽  
Vol 213 ◽  
pp. 106711
Author(s):  
Farid MiarNaeimi ◽  
Gholamreza Azizyan ◽  
Mohsen Rashki
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
High Dimensional ◽  
Nature Inspired Algorithm ◽  
Dimensional Optimization

Improved Embedded Micro-PSO for High-Dimensional Optimization Problems

2012 ◽  
Vol 236-237 ◽  
pp. 1184-1189
Author(s):  
Wen Hua Han ◽  
Chang Dong Zhu
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Small Population ◽  
High Dimensional ◽  
Adaptive Mutation ◽  
Large Scale Optimization ◽  
Continuous Variables ◽  
Scale Optimization ◽  
Dimensional Optimization

This paper presents a novel optimization technique called embedded micro-particle swarm optimization (EMPSO) to solve high-dimensional problems with continuous variables. The proposed EMPSO adopts a population memory which is divided into two portions as the source of diversity, and an external memory to collect particles performing well in an embedded PSO with a very small population size. However, the fact that the new method doesn’t excel in all of the benchmark functions highlights the necessity of developing improvement. Thus an adaptive mutation operator is introduced into EMPSO to remedy the issue. The experimental results show that the improved EMPSO has good performance for solving large-scale optimization problems.

A Novel Modified Tree-Seed Algorithm for High-Dimensional Optimization Problems

2020 ◽  
Vol 29 (2) ◽  
pp. 337-343 ◽  
Author(s):  
Shijie Zhao ◽  
Leifu Gao ◽  
Jun Tu ◽  
Dongmei Yu
Keyword(s):  
Optimization Problems ◽  
High Dimensional ◽  
Dimensional Optimization ◽  
Tree Seed
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