孔云 黄洛锋 资芸 郑磊 田春燕

摘 要 论文针对高校数字资源配置问题，首先设计了研究所需的多目标协同体系;然后设计了数字资源优化配置的多智能体决策框架，将多智能体的主体决策行为与遗传进化算子相结合，构建了多种约束条件下的数字资源智能优化配置模型;最后精选了昆明理工大学图书馆2018年部分数字资源数据进行了模拟实证分析。结果表明：模型能够合理地对研究对象的资源种类占比和类内数据库的配置数量进行多目标协同优化，资源配置的结构和质量得到了较为明显的改善，能够协调不同主体对数字资源的需求，并明显提高了数字资源多目标评价之间的协同水平。

关键词 数字资源;多智能体;遗传算法;优化配置;多目标协同

分类号 G258.6

DOI 10.16810/j.cnki.1672-514X.2022.06.003

Research on Multi Objective Collaborative Intelligent Optimal Allocation Model of Digital Resources in University Library

Kong Yun， Huang Luofeng， Zi Yun， Zheng Lei， Tian Chunyan

Abstract Aiming at the problem of digital resource allocation in universities， this paper first designs the multi-objective cooperation system needed for the research. Then， a multi-agent decision-making framework for the optimal allocation of digital resources is designed. The multi-agent decision-making behavior is combined with genetic evolution operator to construct the intelligent optimal allocation model of digital resources under various constraints. Finally， some digital resource data of Kunming University of Technology Library in 2018 are selected for simulation and empirical analysis. The results show that the model can reasonably carry out multi-objective collaborative optimization on the proportion of resource types of the research object and the allocation quantity of database within the class， the structure and quality of resource allocation have been significantly improved， the needs of different subjects for digital resources can be coordinated， and the collaborative level of multi-objective evaluation of digital resources has been significantly improved.

Keywords Digital resources. Multi-Agent. Genetic algorithm. Optimized allocation. Multi-objective collaboration.

高校图书馆作为大学的文献资源保障中心，是师生全面开展教学科研活动的基础性阵地和进行科技创新活动的重要平台。数字资源作为高校图书馆文献资源的重要组成部分，每年的采购金额、数量和种类都在显著的变化增长[1]。据2020年中国高校图书馆基本统计数据报告显示，2020年电子资源购置费占馆均文献资源购置费的56.8%（2019年是54.6%），均值与比例自2006年以来基本上呈抬升趋势，仅在2019年发生下滑，2020年便恢复上升，表明电子资源的需求相当强劲[2]。如何科学合理地进行数字资源的评估和决策，從而配置满足学校教学科研活动所需的各类数字资源，是高校图书馆决策层面临的重要课题。……