Metaheuristic Algorithms and the Interaction of Natural and Human Domains: The Case of the Imperialist Competitive Algorithm

Introduction: The crucial link between social sciences and engineering impacts societal design and optimization. The Imperialist Competitive Algorithm (ICA), an engineering-proposed optimization tool for social issues, claims to integrate human experiences. This research critically assesses ICA's implied understanding of "natural" and "human" domain interactions and its connection to Iranian-Islamic culture and "Yarygari" (cooperation).
Objective: The main objective is to identify ICA's perspective on the interplay between "natural" and "human" domains.
Methodology: This applied research used a descriptive-analytical, qualitative, and critical library method, reviewing the original ICA thesis and national academic literature.
Findings: ICA models optimization as colonial competition, culminating in a unipolar optimal state. Grounded in social Darwinism, ICA prioritizes speed over sustainability, offering a reductionist view ignoring ecological and human diversity. Its widespread adoption often legitimizes colonialism as social evolution, even in modified versions.
Conclusion: The research concludes ICA's competitive-colonial paradigm is unsustainable. It advocates an alternative based on "Yarygari" (cooperation), drawing on transcendent human values and indigenous Iranian knowledge for ethical, sustainable optimization models.