Abstract
Big bang big crunch (BBBC) optimization algorithm is inspired by theories of evolution of universe. This algorithm completely ignore's various fundamental aspect of big bang big crunch theory, due to which BBBC algorithm has various issues with its conceptual and working structure. These issue's leads to slow convergence and poor solution quality. In view of this, we propose a modified big bang big crunch (MBBBC) optimization algorithm. The effectiveness of this proposed MBBBC is compared with original BBBC and PSO, for six highly nonlinear benchmark functions. Analysis of conducted numerical simulations shows that MBBBC is far better the BBBC, in terms of rate of convergence and solution quality, and MBBBC is on par with PSO.
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