October 29, 2018
Dr. Yunus Emre Yildiz who finished his PhD at Epoka University and Dr. Ali Osman Topal who teaches at Computer Engineering had their research published recently, in one of the top Computer Science journal “Information Sciences” (I.F. : 4.3).
They developed a method to find optimal solutions for 5000 dimensioned large scale problems. They propose micro Differential Evolution with a Directional Local Search (µDSDE) algorithm using a small population size to solve large scale continuous optimization problems. Over the years, many optimization algorithms have been developed to solve such large-scale optimization problems accurately and efficiently.
In this regard, Memetic Algorithms offer robust and efficient framework that hybridizes the Evolutionary Algorithms with a local heuristic search.
In their technique, the best individual retains its position, the second-best individual undergoes mutation and crossover processes of DE, and the rest are reinitialized on the search space. Exploration of the search is carried out with the dispersal of the worst individuals whereas exploitation is performed through DE operators and Directional Local Search (DLS). They conducted extensive empirical studies using two test suites on Large Scale Global Optimization benchmark with up to 5000 dimensions. The results show that µDSDE considerably outperforms existing solutions in terms of the convergence rate and solution quality.
You can reach to the publication from the link below:
https://www.sciencedirect.com/science/article/pii/S0020025516314785
