In the context of accelerating digital transformation, the rationality of resource allocation of the technical service module in the science and technology innovation management system has a vital impact on the system operation efficiency and the smooth progress of scientific research business. At present, the traditional resource allocation method has problems such as insufficient flexibility and difficulty in adapting to complex and changing business needs, which leads to waste of resources and reduced service efficiency. This paper focuses on the resource optimization allocation problem of the technical service module of the science and technology innovation management system. First, it conducts an in-depth analysis of the dilemma of resource allocation in the existing system, and then proposes a resource optimization allocation strategy based on intelligent algorithms. Through the key steps of building a resource demand prediction model, designing an intelligent allocation algorithm, and building a dynamic adjustment mechanism, accurate and efficient resource allocation is achieved. The experimental results verify that the strategy can significantly improve resource utilization and service response speed. Among them, except for P202303, which slightly exceeds the upper limit of 81%, the utilization rates of the rest are basically within the threshold range, which effectively overcomes the defects of traditional resource allocation methods and provides innovative ideas and methods for the optimization of science and technology innovation management systems.

Yinghui Xu, Tingzheng Huang, Lijun Qiu, Chao Wen, Na Xi, Yanyan Duan, Yutian Zhang, Nan Zhang, Dazhong Wang and Yongshuang Zhang. Resource Optimization Allocation Strategy for Technical Service Modules based on Intelligent Allocation Algorithms. International Journal of Big Data Intelligent Technology (2025), Vol. 6, Issue 2: 56-64. https://doi.org/10.38007/IJBDIT.2025.060206.

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