In recent studies, papers related to the multiplicative based numerical methods demonstrate applicability and efficiency of these methods. Numerical root-finding methods are essential for nonlinear equations and have a wide range of applications in science and engineering. Therefore, the idea of root-finding methods based on multiplicative and Volterra calculi is self-evident. Newton-Raphson, Halley, Broyden, and perturbed root-finding methods are used in numerical analysis for approximating the roots of nonlinear equations. In this paper, Newton-Raphson methods and consequently perturbed root-finding methods are developed in the frameworks of multiplicative and Volterra calculi. The efficiency of these proposed root-finding methods is exposed by examples, and the results are compared with some ordinary methods. One of the striking results of the proposed method is that the rate of convergence for many problems are considerably larger than the original methods.

a b s t r a c tAlthough optical multistage interconnection networks (OMINs) promise to meet the ever growing demands of communication networks and multiprocessor systems in fast communication, they suffer from challenges such as path dependent loss and switch crosstalk. In this paper, we propose an innovative approach for reducing not only the path dependent loss but also the number of switch crosstalks in OMINs. Our approach is centered upon modelling OMINs with Petri nets and using the P-invariants method to determine the minimum number of stages m min that is sufficient to establish requested communication patterns in variable-stage OMINs. Being composed of the smallest number of stages and consequently directional couplers (or photonic switches), m min -stage OMIN employs minimal structure and, therefore, path dependent loss and also number of switch crosstalks reach the least possible values in the realization of requested communication patterns.We prove that the size of Petri nets created in this work is in polynomial dependence on the problem size which alleviates memory consumption significantly and ascertains the fact that memory capacity and performance of modern computers are indeed sufficient to run our task. We also show that the complexity results obtained in this research improve similar results reported in our previous paper. We carry out a series of computer experiments to confirm the effectiveness of the proposed approach.