Backtracking Search Algorithm with Lemur Optimizer for Numerical and Global Optimization

The Backtracking Search Algorithm (BSA) stands out as a contemporary stochastic technique that has showcased its prowess in tackling intricate engineering challenges. Thus, a novel hybrid evolutionary algorithm designed to fully leverage the advantages of the BSA and the Lemurs Optimizer (LO). The core objective of this hybrid algorithm is to enhance and discover the global search ability of BSA and provide a robust optimization tool for finding global optima or high-quality solutions for a variety of complex benchmark functions commonly used in the field of optimization. LOBSA's effectiveness has been put to the test with 23 diverse benchmark functions, and its performance has been evaluated through a comparison with highly regarded state-of-the-art competitors. Besides, statistical results indicate that LOBSA presents promising and competitive outcomes, not only for its initial variant but also when compared to the other algorithms.