With the advancement of the knowledge economy, corporate culture has become pivotal for enhancing innovation, development, and soft power within enterprises. This study addresses the optimization of corporate culture management indicators using an innovative approach based on improved multi-objective particle swarm optimization (IMOPSO). Firstly, a comprehensive corporate culture evaluation system was established, integrating multiple key evaluation indicators weighted using the entropy weight method. Secondly, the IMOPSO method was enhanced by incorporating strategies such as Grey Wolf encirclement optimization, competitive variation, and inertia weight optimization. Lastly, the IMOPSO was applied to model and optimize the corporate culture management indicators, thereby enhancing management efficiency. Simulation results validated the effectiveness and feasibility of the proposed method in optimizing corporate culture management indicators.

Ping Zeng, Xiaofei Deng, Chenxi Luo, Jiayao Xu, Juanxia He, Siyu Liu. Optimization Research on Evaluation Indicators of Corporate Culture Management Based on Improved Particle Swarm Algorithm. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 7: 81-89. https://doi.org/10.25236/AJCIS.2024.070711.

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