Slime mould algorithm: A new method for stochastic optimization

Keywords

Computer scienceSMA*Slime moldMathematical optimizationMetaheuristicPath (computing)Set (abstract data type)AlgorithmMathematics

Affiliated Institutions

Related Publications

Harris hawks optimization: Algorithm and applications

Ali Asghar Heidari , Seyedali Mirjalili , Hossam Faris +3 more

2019 Future Generation Computer Systems 5484 citations

Swarms on Sphere: A Programmable Swarm with Synchronous Behaviors like Oscillator Networks

R. Olfati-Saber

In this paper, we introduce a programmable particle swarm evolving on a sphere called swarm on sphere system. This model is a polynomial dynamical system obtained from a consens...

2006 142 citations

A modified particle swarm optimizer

Yibing Shi , R.C. Eberhart

Evolutionary computation techniques, genetic algorithms, evolutionary strategies and genetic programming are motivated by the evolution of nature. A population of individuals, w...

2002 9979 citations

Handbook of Genetic Algorithms

Lawrence Davis

This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems. The first objective is tackled by the editor, Lawrence Davis. Th...

1991 7308 citations

Particle swarm optimization

James Kennedy , R.C. Eberhart

The base isolation design usually used the historical well-known earthquake records as an input ground motion. Through the adjustment on each variables of the structure system, ...

2002 45598 citations

Publication Info

Year: 2020
Type: article
Volume: 111
Pages: 300-323
Citations: 2711
Access: Closed

External Links

Download PDF (Free) View on DOI.org Semantic Scholar

Social Impact

Altmetric

Slime mould algorithm: A new method for stochastic optimization

PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

2711

OpenAlex

174

Influential

2612

CrossRef

Cite This

APA Style

                            
                                    Shimin Li, 
                                
                                    Huiling Chen, 
                                
                                    Mingjing Wang
                                
                                et al.
                            
                            (2020). 
                            Slime mould algorithm: A new method for stochastic optimization. 
                            Future Generation Computer Systems
                            , 111
                            
                            , 300-323.
                            https://doi.org/10.1016/j.future.2020.03.055

Identifiers

DOI: 10.1016/j.future.2020.03.055

Data Quality

Data completeness: 68%