students into the basic principles of using simulation for decision-making. In this introductory note to operations and supply chain simulation using AnyLogic 7.2, the focus is to introduce the MBA and M.Sc. On the other hand, technical issues in development of optimization and simulation models may distract the attention and time from the real objective, i.e., management decision analysis and decision-making support with the help of simulation and optimization software. On one hand, application of optimization and simulation software implies some background in programming. While teaching management students in simulation and optimization classes, it is a challenging task to combine modelling and management decision-making views. Without relying heavily on statistics and mathematical derivations, this guideline offers applied models and a simple, predictable format to make it easy to understand for management students without engineering background. students with majors in supply chain and operations management as well as instructors giving classes in supply chain and operations simulation for such students. Modelling periodic and continuous review inventory control policies with AnyLogic Learning objectives Problem statement Model building EOQ model: event-based simulation Modelling stochastic demand: periodic and continuous review policies Modelling stochastic demand and lead time: re-order point using Java Inventory holding, ordering and stockout costs Re-order point and safety stock Experiments and managerial insights Preparing experiment: using Action Charts Preparing experiment: dynamic target inventory Experiment 1 for engine oil: impact of demand dynamics Experiment 2 for nuts and bolts: impact of lead time dynamics Experiment 3 for nuts and bolts: impact of order quantity Extensions Inventory management in supply chains with production and transportation considerations: system dynamics Agent-based modelling the market demand Literature Discussionĥ Introduction This introductory note was created in order to support MBA and M.Sc. Supply Chain Coordination with AnyLogic Learning objectives Problem statement Model building Create process model Assembler Transport with the help of Conveyor and MoveTo Batch Experiments and managerial insights Part IV Inventory Control 13. Collecting statistics and KPI dashboard design Revenue, costs, profit Resource pool capacity utilization Lead time with the use of time function Total output, completed on time (OTD), delayed and lost orders: usage of Java code for conditions Playing the game Game rules Round # Round # Round #2: Optimization experiment Round #2: Optimization-based simulation experiment Rounds #3 #10 and game evaluation Capacity flexibility analysisĤ Part III Supply Chain Coordination 10. Create custom agent and define rules for order arrival, waiting, and processing: usage of time functions and resource pools Step 3. Business Simulation Game Capacity flexibility simulation with AnyLogic Learning objectives Problem statement Model building Step 1. Playing the game Game rules Round # Round # Round #2: Optimization experiment Round #2: Optimization-based simulation experiment: multiple objective decision making Rounds #3-#10 and game evaluation Further possible extensions and other games Part II Capacity flexibility simulation 7. Collecting statistics and KPI dashboard design Revenue, costs, profit Capacity utilization Lead time and flow time Backlog and queue analysis Experiments and managerial insights Experiment Experiment Experiment Extensions How to introduce the time limits for waiting in the queue Interface creation for playing the game: views, sliders, parameters, variables, functions, and events Views Parameters Variables Functions Events Sliders KPI dashboard creation Resourcesģ 5. Business Simulation Game Process capacity analysis and workload balancing with AnyLogic Learning objectives Problem statement Model building Step 1. 5 Part I Process capacity analysis and workload balancing 1. E-textbook, Berlin School of Economics and Law (preprint). Operations and supply chain simulation with AnyLogic 7.2: Decision-oriented introductory notes for master students. Dmitry Ivanov Berlin School of Economics and Law Professor for Supply Chain Management To be cited as: Ivanov D. 1 Operations and Supply Chain Simulation with AnyLogic 7.2 Decision-oriented introductory notes for management students in master programs Prof.
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