Cooperative co-evolutionary teaching-learning based algorithm with a modified exploration strategy for large scale global optimization

Authors:
Subhodip Biswas;Souvik Kundu;Digbalay Bose;Swagatam Das
Affiliations:
Dept. of Electronics and Communication Engineering, Jadavpur University, Kolkata, India;Dept. of Electronics and Communication Engineering, Jadavpur University, Kolkata, India;Dept. of Electronics and Communication Engineering, Jadavpur University, Kolkata, India;Dept. of Electronics and Communication Engineering, Jadavpur University, Kolkata, India
Venue:
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Year:
2012

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Abstract

Evolutionary Algorithms, inspired from the Darwinian theory on evolution of species, are heuristic method for solving difficult unimodal and multimodal functions. But the ultimate disadvantage of those Evolutionary Algorithms is premature convergence, i.e. trapping in a local optimum due to poor exploration strategy. In case of High Dimensional problems, there are huge chances of convergence prematurely due to the large search space, which grows exponentially with the increase of dimension of the problem. In this paper a modified Teaching-Learning-Based technique is used to investigate the effectiveness of different cooperative co-evolutionary framework for solving high dimensional problems.