Efficient Subpopulation Based Parallel TLBO Optimization Algorithms

Electronics

Héctor Rico¹  José-Luis Sánchez-Romero¹  Antonio Jimeno-Morenilla¹  Alejandro García-Monzó²  Héctor Migallón²  RavipudiVenkata Rao³ 

[1] Department of Computer Technology, University of Alicante, E-03071 Alicante, Spain;Department of Physics and Computer Architecture, Miguel Hernández University, E-03202 Alicante, Spain;Sardar Vallabhbhai National Institute of Technology, Surat 395 007, Gujarat State, India;

关键词: TLBO;    optimization problems;    parallel;    heuristic;    subpopulations;    OpenMP;    MPI;    hybrid MPI/OpenMP;   

DOI  :  10.3390/electronics8010019

来源: DOAJ

【 摘 要 】

A numerous group of optimization algorithms based on heuristic techniques have been proposed in recent years. Most of them are based on phenomena in nature and require the correct tuning of some parameters, which are specific to the algorithm. Heuristic algorithms allow problems to be solved more quickly than deterministic methods. The computational time required to obtain the optimum (or near optimum) value of a cost function is a critical aspect of scientific applications in countless fields of knowledge. Therefore, we proposed efficient algorithms parallel to Teaching-learning-based optimization algorithms. TLBO is efficient and free from specific parameters to be tuned. The parallel proposals were designed with two levels of parallelization, one for shared memory platforms and the other for distributed memory platforms, obtaining good parallel performance in both types of parallel architectures and on heterogeneous memory parallel platforms.

【 授权许可】

Unknown