多源并发协同物流网络随机任务与共享资源动态调配研究

It is increasingly challenging for task-resource assignment in collaborative logistics network facing logistics resource conflicts caused by random concurrency of logistics tasks. In this situation, decision making optimization and conflict resolution of task-resource assignment need to be explored. This research mainly studies the dynamic assignment decision and control problem for random tasks with shared resources in collaborative logistics network under multi-source concurrency. Firstly, it refines the internal and external key impact factors of task-resource assignment, and analyzes the complex coupling relationship between multiple factors. The uncertain interpretation of task-resource assignment is investigated from exogenous and endogenous. Secondly, considering the characteristics of completely uncertain problem about concurrent task-shared resource assignment in single cycle, a multi-objective optimization decision making model is presented for progress deviation early-warning and adjustment control in multi-stage implementation of assignment plan. It reveals the robustness optimization principle of uncertain decision and control in signal circle task-resource assignment. Thirdly, in order to solve the problem of conflict resolution about random task-shared resource assignment in multiple circles, it explores the equilibrium resolution strategy for task-resource assignment conflicts. Finally, combining the actual cases of enterprises, it proposes the flexible coping scheme of task-resource assignment in collaborative logistics network resources. The research results significantly provide theoretical and decision support for the orderly and efficient operation of collaborative logistics network and other similar virtual organizations. Also, it is of great significance to enrich and develop the related theories and methods of dynamic task-resource assignment.

物流任务随机并发带来的物流资源冲突是协同物流网络任务-资源调配所面临的严峻挑战，该挑战下调配优化决策与冲突消解亟待探索。本项目主要研究多源并发协同物流网络随机任务与共享资源的动态调配决策与控制问题。首先，提炼影响任务-资源调配内外部关键因素，解析多因素间耦合作用关系，对不确定作用影响进行“外源性”和“内生性”诠释。其次，考虑单周期内并发任务-共享资源调配的完全不确定问题特质，构建调配多目标优化决策模型，对调配方案多阶段实施进行进度偏差预警和调整控制，揭示单周期调配不确定决策与控制的“鲁棒性”优化原理。进而，针对多周期间随机任务-共享资源调配的关联冲突消解问题，探索调配冲突的“均衡性”消解策略。最后，结合企业实际案例，提出协同物流网络调配柔性应对方案。项目研究成果可为促进协同物流网络及其他类型虚拟组织调配有序高效运行提供理论支撑和决策支持，对丰富和发展动态调配相关理论和方法体系具有重要意义。

本项目主要研究多源并发协同物流网络随机任务与共享资源的动态调配决策与控制问题。主要研究内容分为四个部分：（1）多源并发协同物流网络随机任务与共享资源调配内外部影响因素分析；（2）外部随机需求不确定影响机制与内部共享资源竞合性响应机理研究；（3）单周期内并发任务-共享资源闭环调配的可行方案优选与实施控制研究；（4）多周期间随机任务-共享资源开环调配的关键冲突识别与消解均衡研究。.在该项目的资助下，项目负责人出版学术专著1部，以第一作者/通讯作者在 IEEE Transactions on Fuzzy Systems、Information Sciences、Computers & Industrial Engineering、管理科学学报、中国管理科学等管理科学领域高质量期刊发表论文18篇，其中，ESI全球热点论文1篇、高被引论文5篇、人大复印报刊资料全文转载2篇。研究成果得到了中国科学院汪寿阳研究员（发展中国家科学院院士、国际系统与控制科学院院士）、香港城市大学Kwai-Sang CHIN教授（国际质量科学院院士）、厦门大学林伯强教授（Energy Economics 主编）等同行专家好评。.项目负责人荣获山东省社会科学优秀成果奖、山东省高等学校人文社会科学优秀成果奖、青岛市第社会科学优秀成果奖、中国石油软科学优秀成果奖等。项目组成员积极参与国内外学术交流，例如，承办International Conference on Intelligent Transportation and Logistics with Big Data、中国预测前沿学术论坛，参加The 11th Workshop on Risk Correlation Analysis and Risk Measurement、The 4th Workshop on Scientific data analysis and decision making、第四届计算金融与管理国际会议并做大会报告或邀请报告；邀请德克萨斯大学达拉斯分校的Metin教授、齐安焱副教授和葡萄牙里斯本大学的Francisco副教授等访问实验室，并做学术报告。.研究成果提出了具有中国特色的智能配送系统解决方案，帮助生产&销售企业实现降本增效和业务转型升级，并助力双碳目标实现，具有重要的现实意义。

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