![]() Optimization means to find the optimal and diverse solution for a complex problem ( Bengio, Lodi & Prouvost, 2020). Moreover, we evaluate our results with the best known dynamic programing and arithmetic multiplication approaches, which clearly demonstrate that proposed model outperforms in terms of computational time and space complexity. ![]() The proposed model provides good performance and reduces the multiplication operations varying from 45% to 96% when compared with sequential multiplication. Our experimental results and their analysis show that the proposed GCO model has achieved significant reduction of time with efficient speed when compared with sequential chain matrix multiplication approach. ![]() In this article, we proposed a new model to minimize the Chain Matrix Multiplication (CMM) operations based on group counseling optimizer (GCO). However, these techniques are deficient for providing optimal results for CMMP in terms of computational time and significant amount of scalar multiplication. For CMMP the researchers have proposed various techniques such as dynamic approach, arithmetic approach, and sequential multiplication. ![]() This problem arises in various scientific applications such as in electronics, robotics, mathematical programing, and cryptography. The Chain Matrix Multiplication Problem (CMMP) is an optimization problem that helps to find the optimal way of parenthesization for Chain Matrix Multiplication (CMM).
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