Software


 

Software1: Basic PIO algorithm

Developers: Peixin Qiao, and Haibin Duan.

Short description: This software provides an implementation of Pigeon-Inspired optimization (PIO)
algorithm for solving complex optimization functions. It contains two operators by using some rules.

Programming language: Developed in Matlab under Windows. The basic PIO software is available HERE.

 

Software2: Bloch Quantum-behaved PIO (BQPIO)

Developers: Honghao Li, and Haibin Duan.

Short description: BQPIO is a novel hybrid Pigeon Inspired Optimization (PIO) and quantum theory. Quantum theory is adopted to increase the local search capacity as well as the randomness of the position. The improved BQPIO can avoid the premature convergence problem and find the optimal value correctly when solving multimodal problems.

Programming language: Developed in Matlab under Windows. The BQPIO software is available HERE.

 

Software3: PID Controller Design Based on Prey-Predator PIO Algorithm

Developers: Hang Sun, and Haibin Duan.

Short description: PID Controller Design based on Prey-Predator PIO algorithm combines the standard Pigeon-Inspired Optimization algorithm and the Prey-Predator strategy. This new algorithm can avoid the disadvantage which standard Pigeon-Inspires optimization has. Comparative experiments on the Proportion-Integral-Derivative (PID) parameter adjustment are conducted by using Particle-Swarm Optimization (PSO), PIO and Prey-Predator PIO, and the comparative results demonstrate the proposed approach is more feasible and effective.

Programming language: Developed in Matlab under Windows. The PPPIO software is available HERE.

 

 

Bio-inspired Autonomous Flight Systems (BAFS) Research Group, School of Automation Science and Electrical Engineering,

Beihang University (BUAA), Beijing, PR China

 
Ant Colony Bee Colony

Gen String

Pigeons
Fish Schooling
Bird Flocking
UAS
Swarm Robots

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Last modified: July 9 2018 12:19:27