Abstract
Gravitational search algorithm is a newly born metaheuristic which is inspired by the working force of attraction between two masses. In this article gravitational search algorithm is employed to solve the constrained optimization problems. A variety of state-of-the-art benchmark problems are taken into account to justify the performance of the gravitational search algorithm. The results of gravitational search algorithms are compared with two state-of-the-art Particle Swarm Optimization algorithms in various aspects. Pairwise one tailed t test is applied to justify the statistical significance of the results and time complexity analysis is also performed. Finally the conclusions are drawn based on the experimental results.
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