Parallelization-of-Optimizers-for-Single-Objective-Functions

Single objective optimization algorithms are the basis of the more complex optimization algorithms such as multi-objective, dynamic, constrained optimization algorithms and so on. Research on single objective optimization algorithms influence the development of the optimization branches mentioned above. In the recent years, various kinds of novel optimization algorithms have been proposed to solve real-parameter optimization problems. Our project aims to parallelize such optimizers for solving single objective problems with the help of threading libraries. Evaluation of the performance of these optimizers on specific problems can be studied under different constraints as a part of a larger framework, to improve performance of the algorithms and better understand the suitability of the same.

This project was done as part of J-Component in Parallel and Distributed Computing