Supply Chain Simulation
本课程教授如何运用计算机仿真技术分析和优化复杂供应链系统。课程内容包括离散事件仿真基础、排队论与系统动力学、输入数据建模与分布拟合、仿真输出分析与验证、供应链牛鞭效应仿真、仓储系统仿真、生产系统仿真、物流配送网络仿真等。学生将学习使用专业仿真软件（如Arena、AnyLogic、FlexSim或Python SimPy）建立供应链模型，设计仿真实验，并通过数据分析支持决策。
This course teaches how to use computer simulation technology to analyze and optimize complex supply chain systems. Topics include discrete event simulation fundamentals, queuing theory and system dynamics, input data modeling and distribution fitting, simulation output analysis and validation, bullwhip effect simulation, warehouse system simulation, production system simulation, and logistics network simulation. Students learn to use simulation software (Arena, AnyLogic, FlexSim, or Python SimPy) to build supply chain models and design experiments.
构建一个包含供应商、制造商、分销商、零售商的四级供应链仿真模型。在需求随机波动的条件下，模拟不同信息共享策略（无信息共享、部分共享、完全共享）和库存策略下的牛鞭效应。通过大量重复实验，收集各层级的订货量方差、库存水平、服务水平和总成本数据。运用统计方法分析不同策略对牛鞭效应的抑制效果，提出最优的供应链协同策略。提交仿真模型、实验数据和分析报告。
Build a four-level supply chain simulation model with supplier, manufacturer, distributor, and retailer. Simulate the bullwhip effect under different information sharing strategies (no sharing, partial sharing, full sharing) and inventory policies with stochastic demand. Through extensive replication, collect data on order variance, inventory levels, service levels, and total costs at each echelon. Use statistical analysis to evaluate strategy effectiveness and propose the optimal supply chain coordination strategy.