A Binary Black Widow Optimization Algorithm for Addressing the Cell Formation Problem Involving Alternative Routes and Machine Reliability

The Cell Formation Problem (CFP) involves the clustering of machines to enhance productivity and capitalize on various benefits. This study addresses a variant problem where alternative routes machine reliability are included, which we call Generalized with Machine Reliability (GCFP-MR). is known be NP-Hard, finding efficient solutions utmost importance. Metaheuristics have been recognized as effective optimization techniques due their adaptability ability generate high-quality in short time. Since BWO was originally designed for continuous problems, its adaptation binarization. Accordingly, our proposal focuses adapting Black Widow Optimization (BWO) metaheuristic tackle GCFP-MR, leading new approach named Binary (B-BWO). We compare two ways. Firstly, it benchmarked against previous Clonal Selection Algorithm approach. Secondly, evaluate B-BWO parameter configurations. experimental results indicate that best configuration parameters includes population size (Pop) set 100, number iterations (Maxiter) defined 75. Procreating Rate (PR) at 0.8, Cannibalism (CR) 0.4, Mutation (PM) also 0.4. Significantly, proposed outperforms state-of-the-art literature’s result, achieving noteworthy improvement 1.40%. reveals efficacy solving GCFP-MR potential produce superior compared methods.