‘Partly'globalized networks and driving mechanism in resource-based state-owned enterprises:A case study of J Group

In the context of economic globalization,while multinational enterprises from developed countries occupy a high-end position in the global value chain,enterprises from developing countries are often marginalized in the world market.In China,resource-based state-owned enterprises(SOEs)are tasked with the mission of safeguarding resource security,and their internationalization development ideas and strategic deployment are significantly and fundamentally different from those of other non-state-owned enterprises and large multinational corporations.This study provides ideas for the globalization policies of enterprises in developing countries.We consider J Group in western China as a case and discuss its productive investment and global production network development from 2010 to 2019.We found that J Group was‘Partly'globalized,and there are multiple core nodes with the characteristics of centralized and decentralized coexistence in the production network;in addition,the overall layout centre shifted to Southeast Asia and China;however,its global production was restricted by the enterprise's investment security considerations,support and restrictions of the home country,political security risk of the host country,and sanctions from the West.These findings provide insights for future research:under the wave of anti-globalization and'internal circulation as the main body',resource SOEs should consider the potential risk of investment,especially keeping the middle and downstream industrial chain in China as much as possible.

基于空间颗粒模型的电商三维装箱智能决策研究

在电商仓储中,对于不规则物品打包作业属于特殊的三维装箱问题(three dimensional bin packing problem,3D-BPP),需要选择箱子的种类和数量,确定物品的装箱位置和方向,以期最大化利用装载空间。本文采用点云刻画不规则物品的形状,通过颗粒化的思想,将稀疏不均匀的点云转化为不规则物品的空间颗粒凸包,构建了不规则物品三维装箱问题的空间颗粒模型;通过提炼装箱活动实践操作的专家规则,设计了基于经验模拟的启发式算法,并结合DQN(deep q-network)算法框架设计了针对不规则物品三维装箱问题的H-DQN(heuristic deep q-network)算法。此外,本文基于现有行业数据,开发了一个实例生成器用于算例测试。数值测试结果表明,相较于遗传算法等已有算法,H-DQN算法的空间利用率平均提高到45.92%;同时计算速度明显加快,平均降低了97%的计算时间,验证了H-DQN算法处理3D-BPP的有效性。