Improved Pigeon-inspired Optimization Algorithm Based on Human Behavior and t-distributed Mutation Strategy
NI Yunfeng
LIANG Jiahao
WANG Jing
GUO Ping
Abstract：To address the shortcomings of the pigeon-inspired optimization algorithm(PIO)with weak global search ability and falling into local optimal solutions easily,this paper proposes an improved pigeon-inspired optimization algorithm,which com-bines human behavior strategy and t-distribution mutation strategy.The map compass operator is improved by human behavior strate-gy to realize the diversity of population distribution,and the landmark operator is improved by t-distribution mutation strategy to im-prove the exploration and development capability of the algorithm.Combining the two strategies,the improved pigeon-inspired opti-mization algorithm has stronger ability to jump out of local extremum and higher global searcher accuracy.Comparing with the pi-geon-inspired optimization algorithm(PIO),other five algorithms and other scholars improved PIO on 11 test functions,the experi-mental results show that the improved pigeon-inspired optimization algorithm with two improved strategies has better convergence precision and faster convergence speed.
Keywords：improved pigeon swarm search operatorhuman behaviort-distributionglobal searchinglocal searching
Publication Date：2024-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 3555-3561 )