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In Artificial Intelligence, numerical optimization is an instantly rising research domain. Swarm Intelligence (SI) and Evolutionary Algorithm (EA) are widely used to answer the problems where the optimal solution is required. Inspired by Seagull’s natural behavior, the Seagull Optimization Algorithm (SOA) is a meta-heuristic, swarm-based intelligent search method. SOA algorithm is a population-based intelligent stochastic search procedure that inherited the manner of seagulls to seek food. In SOA, population initialization is crucial for making rapid progress in a d-dimensional search space. In order to address the issue of premature convergence, this research presents a new variation called the Adaptive Seagull Optimization Algorithm (ASOA). Second, a variety of starting methods have been suggested as ways to enhance seagulls’ propensity for exploratory activity. To improve the diversity and convergence factors …