Intelligent optimization algorithm for strategic planning in economics with multi-factors assessment: A MEREC-driven Heronian mean framework

Strategic planning in economics solves interconnected challenges such as dynamic interdependencies, conflicting objectives, and uncertain outcomes. Many such complexities present challenges for traditional approaches in terms of the evaluation and outcomes, requiring an innovative decision approach. An intelligent optimization algorithm is introduced in this paper, which assists policymakers in strategic planning through a multi-factor comprehensive assessment. A robust mechanism for analyzing, prioritizing, and resolving conflicting objectives is proposed based on integrating economic, social, and risk-related parameters within a highly sophisticated circular interval-valued framework. Unlike the traditional model, the proposed methodology is applied to reveal more adaptive, dynamic, and interdependent factors that provide actionable strategies that are consistent with policy goals. The comparison analysis demonstrates the proposed algorithm's validation and efficacy, highlighting the reliability and adaptability and depicting that the algorithm can transform the process of making economic strategy. The proposed work provides theoretical innovation and practical applications such as macroeconomic policy, financial risk management, and sustainable infrastructure development. It is a compelling tool for policymakers and strategists seeking to maximize economic outcomes in uncertain and dynamic environments.