Abstract:

In this study, we introduce the Numidian Cavalry-Inspired Swarm Optimization (NCSO) approach, which takes cues from the agile and strategic maneuvers of the ancient Numidian Cavalry. The NCSO algorithm mirrors the speed and adaptability by implementing a communication and decision-making mechanism, enabling rapid navigation through complex optimization landscapes. Unlike precision-focused algorithms, the NCSO prioritizes speed, making it a valuable complement to more precise optimization methods. This swarm intelligence-based algorithm embodies the essence of the Numidian Cavalry's tactics, swiftly adapting and iterating to enhance efficiency in challenging optimization tasks. In our evaluation, we assess the NCSO algorithm's performance against various established optimization methods, highlighting its impressive convergence speed and competitive solution quality. These results underscore the potential of swarm-based optimization algorithms to transform problem-solving, particularly when influenced by historical military strategies. While the NCSO algorithm may trade precision for velocity, its role as a tool to accelerate the optimization process is crucial, demonstrating the powerful synergy achievable by merging historical insights with modern computational approaches.