Natural phenomenon can be used to solve complex optimization problems with its excellent
facts, functions, and phenomenon. In this paper, a survey on physics‐based algorithm is …

A novel computer aided method is presented that yields Linear Time Invariant Reduced
Order System (LTI-ROS). This is accomplished by using the combined benefits of Big Bang …

A new method of model order reduction is introduced by combining the merits of big bang
big crunch (BBBC) optimization technique and stability equation (SE) method. A linear …

In this study, an inverse controller based on a type-2 fuzzy model control design strategy is
introduced and this main controller is embedded within an internal model control structure …

The use of inverse system model as a controller might be an efficient way in controlling non-
linear systems. It is also a known fact that fuzzy logic modeling is a powerful tool in …

A new approach to parameter estimation of structural systems using the recently developed
Big Bang-Big Crunch (BB-BC) optimization is proposed, in which the parameter estimation is …

Nature-Inspired Computing: Physics and Chemistry-Based Algorithms provides a
comprehensive introduction to the methodologies and algorithms in nature-inspired …

In the recent years it has been demonstrated that type-2 fuzzy logic systems are more
effective in modeling and control of complex nonlinear systems compared to type-1 fuzzy …

Nowadays, nature-inspired metaheuristic algorithms are the most powerful optimizing
algorithms for solving NP-complete problems. This paper proposes five recent approaches …

This paper presents the performance of Parallel Big Bang–Big Crunch (PB3C) global
optimization algorithm on CEC-2014 test suite. The performance is compared with 16 other …