Reliability Optimization of Linear and Linear Consecutive K-Out-Of-N Systems Using Teaching-Learning-Based Optimization and Genetic Algorithm - Sazak, Şefika Büşra; Elmastaş Gültekin, Özge (International Journal of Industrial Engineering: Theory, Applications and Practice, 2025)
Numerous engineering applications involve ensuring the proper functioning of systems, minimizing errors, and optimizing the system and its subcomponents. Achieving desirable outcomes often requires enhancing positive factors through optimization methods while mitigating negative factors. In this context, metaheuristic algorithms are favored to find solutions aligned with the intended objectives. Among such algorithms, Teaching-Learning Based Optimization (TLBO) and Genetic Algorithm (GA) stand out, drawing inspiration from real-life processes. This study focuses on applying the TLBO algorithm to optimize the reliability of linear k-out-of-n: F and G (lin/k/n: F and lin/k/n:G) and linear consecutive k-out-of-n: F and G (lin/con/k/n:F and lin/con/k/n:G) systems. Additionally, the system was analyzed using GA, and the results from both approaches were compared. By employing these powerful metaheuristic algorithms, we aim to attain effective and robust solutions for enhancing system reliability and performance. Also, this study can be a guide in terms of contributing to the reduction of costs by ensuring more efficient use of resources, especially in complex systems. It can also increase productivity by reducing labor by ensuring the efficient operation of machines and processes.