Carpet Weaver Optimization: A Novel Simple and Effective Human-Inspired Metaheuristic Algorithm.

In this paper, a new human-based metaheuristic algorithm called Carpet Weaving Optimization (CWO) is introduced, which is inspired by human skills when weaving a carpet. The main source of inspiration in the design of CWO is taken from the communication between the carpet weaver and the map reader who try to weave a carpet according to the given pattern. The theory of CWO is stated and then mathematically modeled based on the simulation of the carpet weaving process. The effectiveness of CWO in optimization has been assessed across twenty-three standard benchmark functions encompassing unimodal, high-dimensional multimodal, and fixed-dimensional multimodal categories. The optimization outcomes underscore CWO's capability to yield favorable results across various optimization challenges, adeptly navigating between exploration, exploitation, and achieving a balanced search process. Comparative analysis against twelve rival algorithms demonstrates CWO's superior performance, consistently outshining competitors across all twenty-three benchmark functions and securing the top rank as the premier optimizer. Moreover, the efficacy of CWO in real-world applications has been scrutinized through its optimization of four engineering design quandaries. Simulation findings corroborate CWO's commendable performance in real-world and engineering contexts, as evidenced by its capacity to deliver superior values for design variables and objective functions compared to competing algorithms. [ABSTRACT FROM AUTHOR]