Design Engineering ISSN: 0011-9342 | Year 2021 Issue: 8 | Pages: 4751-4763 [4751] A Black Widow Optimization Algorithm Using Chaos Reproduction Operator Alaa Mokhtar 1 *, Hegazy Zaher 2 , Naglaa Ragaa 3 , Eman Mostafa 4 1 Ph.D. Researcher of Operations Research, faculty of graduate studies for statistical research, Cairo University, Cairo, Egypt 2 Professor of Mathematical statistics, faculty of graduate studies for statistical research, Cairo University, Cairo, Egypt 3 Professor of Operations Research, faculty of graduate studies for statistical research, Cairo University, Cairo, Egypt 4 Asistant Professor of Operations Research, faculty of graduate studies for statistical research, Cairo University, Cairo, Egypt *Corresponding Author: Alaa Mokhtar Abstract: Nature-inspired optimization algorithms can solve different scientific and engineering problems. Recently, metaheuristic algorithms are becoming powerful methods for solving NP problems. Black Widow Optimization (BWO) algorithm, is inspired by the mating behavior of black widow spiders. In this paper, a proposed more efficient algorithm for black widow optimization algorithm using a chaotic reproduction operator is proposed. Some experiments have been performed to study chaotic modernization in simulations of evolution. Three different algorithms are proposed; the first algorithm is called speedy, the second algorithm is called periodic and The third algorithm is called chaotic. The second order logistic function with one parameter is used to show the chaotic behavior. Obtained results show the efficiency that the proposed algorithms are more efficient than the old ones. Keywords: Optimization, Chaos, Black Widow Optimization Algorithm, Logistic Function. I. INTRODUCTION Recently, due to the high complexity of real-world problems, the need for efficient meta heuristic methods emerges. Metaheuristic methods on account of their high efficiency and easy implementation become extremely popular. Objective functions may have many global optimizations, i.e. every objective function can have similar values at several different points in the explored state space. In addition, some local optimal points for which the objective function values lie close to the global optimum level. Real-world problems are categorized as problems with improving multimedia functionality. David (1989) believes in the state space at a lot of different points have the similar values for the objective function may . Also, it may contain some local optimal points lie near from the global optimum [1].