Vector GA: a novel enhancement of genetic algorithms for efficient multi-variable or multi-dimensional search

Authors:
Indrajit Bhattacharyya;Anup Kumar Bandypopadhyay;Bhaskar Gupta;Aloknath Chattopadhyay;Rajeswari Chattopadhyay;Kiyotoshi Yasumoto
Affiliations:
Jadavpur University, Kolkata, India;Jadavpur University, Kolkata, India;Jadavpur University, Kolkata, India;New Technology Applications, Bangalore, India;New Technology Applications, Bangalore, India;Kyushu University Fukuoka, Japan
Venue:
ACM SIGSOFT Software Engineering Notes
Year:
2009

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Abstract

Many software engineering problems can be viewed as a large multidimensional searching problem. This paper presents an enhancement of conventional Genetic Algorithms (GA) for more efficient multi-variable or multi-dimensional searches. The concept relies upon expressing chromosomes as vectors in the required multidimensional frame of reference. Usual GA operators are also defined as vector operators. Comparison with conventional genetic algorithm is made to illustrate its superior performance.