Enhancing Parrot Optimizer Performance with Genetic Algorithm Integration for Solving the N-Queens Problem

Abstract

In this paper, a new hybrid optimization algorithm using a combination of Parrot Optimizer (PO) and Genetic Algorithm (GA) is proposed to efficiently solve the N-Queens problem. The Parrot Optimizer, based on the social behavior and communication of parrots, exhibits high exploitation ability but premature convergence; low exploration limitations are present. These complexities affect its performance in challenging combinatorial problems such as the N-Queens problem, where a fine trade-off between exploration and exploitation is required. By incorporating GA's powerful exploration mechanism—crossover and mutation operations—this hybrid model enriches the solution space and reduces the possibility of being trapped in a local optimum. Experimental results show that the proposed hybrid algorithm achieves much better solution quality and better convergence speed than single use of Parrot Optimizer and Genetic Algorithm. These results contribute to developing new efficient optimization approaches for combinatorial problems, showing the potential of integrating different metaheuristics.