Research on multidimensional data fusion and algorithm optimization methods in engineering management decision making

With the increasing complexity of engineering management, traditional decision-making methods are often difficult to cope with the challenges of multi-dimensional and multi-source data, relying on data engineering construction to promote quality refinement and control, which has become a key means to enhance the quality control capability of equipment in the context of digital research and development. The purpose of this paper is to study the application of multidimensional data fusion and algorithm optimization in engineering management decision-making, and to improve the accuracy and efficiency of decision-making by integrating different types of data sources. Common data types in engineering management and the challenges they face are analyzed, and the necessity of data fusion is discussed. A decision support system framework for engineering management based on data fusion is proposed, focusing on the integration and fusion methods of multidimensional data and its optimization techniques. The decision support system is designed in combination with optimization algorithms to improve the decision quality and rationality of resource allocation in the engineering management decision-making process. The method can effectively improve the accuracy and real-time of engineering management decision-making, and has a wide range of application prospects. Through the optimization and innovation of existing technology, this paper provides a new solution for engineering management decision-making and lays the foundation for the design and development of future intelligent decision-making system.