The revised stochastic simplex bisection algorithm and particle swarm optimization

• Autorzy: Samuelsson Christer

Identyfikatory

DOI

10.15439/2017F119

• Konferencja: Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems
• Języki publikacji: EN

Abstrakty

EN

The stochastic simplex bisection (SSB) algorithm is evaluated against particle swarm optimization (PSO) on a prominent test set. The original SSB algorithm performs on par with the PSO algorithm and a revised version of the SSB algorithm outperforms both of them. Detailed analysis of the performance on select objective functions brings to light key properties of the three algorithms. The core SSB algorithm is here viewed as a sampling tool for an outer loop that employs statistical pattern recognition. This opens the door for a host of other schemes.

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2017
• Tom: Vol. 13
• Strony: 103--110
• Opis fizyczny: Bibliogr. 26 poz., tab.

Twórcy

autor

Samuelsson Christer

• 25A rue des Sports, 57200 Sarreguemines, FRANCE

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