Title
A neighbor-based learning particle swarm optimizer with short-term and long-term memory for dynamic optimization problems.
Abstract
This paper presents a novel Particle Swarm Optimization algorithm to address Dynamic Optimization Problems. The algorithm incorporates a neighbor-based learning strategy into the velocity update of Particle Swarm Optimization, in order to enhance the exploration and exploitation capabilities of particles. Unlike the traditional swarm update scheme, a “worst replacement” strategy is used to update the swarm, whereby the position of the worst particle in the swarm is replaced by a better newly generated position. The short-term memory is employed to store solutions with intermediate fitnesses from the most recent environment, and the long-term memory is to store the historical best solutions found in all previous environments. After an environmental change is detected, some particles’ positions in the swarm are replaced by the members of the short-term memory, and the best member in the long-term memory under the current environment is re-introduced to the active swarm along with its Gaussian neighborhood, then the remaining particles’ positions are re-initialized. The performance of the proposed algorithm is compared with six state-of-the-art dynamic algorithms over the Moving Peaks Benchmark problems and Dynamic Rotation Peak Benchmark Generator. Experimental results indicate that out algorithm obtains superior performance compared with the competitors.
Year
DOI
Venue
2018
10.1016/j.ins.2018.04.056
Information Sciences
Keywords
Field
DocType
Neighbor-based learning,Particle swarm optimization,Worst-replacement,Short-term and long-term memory,Dynamic optimization problems
Particle swarm optimization,Mathematical optimization,Swarm behaviour,Gaussian,Artificial intelligence,Long-term memory,Optimization problem,Machine learning,Mathematics,Particle,Particle swarm optimizer
Journal
Volume
ISSN
Citations 
453
0020-0255
7
PageRank 
References 
Authors
0.45
37
3
Name
Order
Citations
PageRank
Leilei Cao1312.78
Lihong Xu234436.70
Erik Goodman314515.19