Cross-Domain Intelligent Optimization and System Resilience Architecture: From Recommendation Algorithms to TCM Standardization and Chemical Engineering Multidimensional Applications
As information systems continue to experience exponential growth in complexity, cross-domain intelligent optimization and system resilience architecture have emerged as frontier topics in modern engineering and medical research. This paper systematically reviews research directions including resource optimization in multidimensional recommendation systems, resilience guarantee mechanisms for large-scale concurrent platforms, machine learning-driven logistics network optimization, standardization of traditional Chinese medicine external therapies, and intelligent response systems in chemical engineering. The study reveals deep methodological commonalities across these seemingly heterogeneous domains. Research demonstrates that submodular constraint-based optimization frameworks, predictive multidimensional safeguard mechanisms, knowledge graph-driven intelligent response systems, and multi-objective optimization algorithms exhibit significant efficacy in their respective fields, providing theoretical foundations and practical pathways for constructing cross-domain intelligent system resilience architectures. By integrating multidisciplinary research findings, this paper proposes a general methodological framework for resilience optimization applicable to complex systems.
