A Novel Particle Swarm Optimization with Improved Learning Strategies and Its Application to Vehicle Path Planning
In order to balance the exploration and exploitation capabilities of the PSO algorithm to enhance its robustness, this paper presents a novel particle swarm optimization with improved learning strategies (ILSPSO). Firstly, the proposed ILSPSO algorithm uses a self-learning strategy, whereby each par...
Main Authors: | En Lu, Lizhang Xu, Yaoming Li, Zheng Ma, Zhong Tang, Chengming Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2019-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/9367093 |
Similar Items
-
Greedy Mechanism Based Particle Swarm Optimization for Path Planning Problem of an Unmanned Surface Vehicle
by: Junfeng Xin, et al.
Published: (2019-10-01) -
Three-Dimensional Path Planning for Unmanned Aerial Vehicle (UAV) Based on Quantum-Behaved Particle Swarm Optimization
by: Tsai, Cheng-En, et al.
Published: (2014) -
Hybridizing Particle Swarm Optimization and Differential Evolution for the Mobile Robot Global Path Planning
by: Biwei Tang, et al.
Published: (2016-05-01) -
An Improved Method of Particle Swarm Optimization for Path Planning of Mobile Robot
by: Xun Li, et al.
Published: (2020-01-01) -
Study of Particle Swarm Optimization Algorithm for Optimal Robot Path Planning
by: You-Yu Huang, et al.
Published: (2013)