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Screening Methods in Simulation for Logistics: A Case Study from DASE

This chapter focuses on screening methodologies used in the field of logistics simulation, illustrating the process through a case study involving a supply chain scenario. It discusses the aggregation of factors, experimentation with grouped variables, and the importance of identifying significant interactions. The screening process resulted in narrowing down 92 factors to 10 remaining variables after testing 19 simulated input combinations. Key assumptions, such as first-order polynomial effects and strong heredity, are also addressed, providing foundational knowledge for logistics optimization.

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Screening Methods in Simulation for Logistics: A Case Study from DASE

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  1. Chapter 6 (DASE):Screening Jack P.C. Kleijnen Course ‘Simulation for Logistics’ 2008 Technical University Eindhoven November 18 DASE Chapters 6 TUE 2008

  2. SB metaphor: lake, dam & rocks DASE Chapters 6 TUE 2008

  3. Screening: SB Example: supply chain; 92 factors; 10 factors remain after 19 simulated input combinations Procedure (also see previous Figure): • Aggregate factors into groups • Experiment (simulate) with group factors • Split important groups; ignore unimportant SB assumptions: • 1st-order polynomial & two-factor interactions • Known positive signs: no canceling out • ‘Strong heredity’: b(j) = 0 → b(j, j’) = 0 DASE Chapters 6 TUE 2008

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