This paper introduces a novel hybrid optimization algorithm, BB-CFO, which combines the big bang-big crunch (BB-BC) and central force optimization (CFO) algorithms to address key challenges in Internet of Things (IoT) networks, such as energy constraints, delay, and scalability. The proposed BB-CFO algorithm improves both the exploration and exploitation phases of optimization, providing a balanced approach for solving complex routing problems in low-power and lossy networks. The algorithm is integrated into the quality fuzzy routing protocol for low-power and lossy networks (Q-FRPL), which is evaluated through extensive simulations using Cooja and NS2 environments. The contributions of this study are twofold: first, the development of a hybrid optimization technique that enhances routing efficiency in IoT networks, and second, the demonstration of its effectiveness through comparative analysis with conventional algorithms. ...