Investigating the Efficiency of Parallel Algorithms for Stochastic Optimization
Marat Voronukhin, Valery A. Zasov · 2019
The paper presents the results of investigating the efficiency indicators of two parallel algorithms for stochastic optimization-the genetic algorithm and the particle-swarm algorithm. The paper discusses experimental relationships for the efficiency indicators of the parallel algorithms: runtime, acceleration, error, and solution stability, depending on the type and dimension of the target function, the number of agents used, and processor cores. The comparative estimates for the algorithms are given.