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Introduction to Simulation - Coggle Diagram
Introduction to Simulation
Core Definition & Concepts
Model
Set of system assumption
Entities
Objects of interest
Simulation
Imitation of a real-world process or system over time
Measures of performance
When Simulation is Appropriate
Experimentation
Observe effects of informational, organisational, or environmental changes
Test new designs / policies before implementation
System Design
Determine machine requirements by simulating capabilities
Visualise plans through animation
Analysis & Learning
Identify important variables and how they interact.
Verify analytic solutions
Pedagogical device to reinforce analytic methodologies
Training without cost/disruption of on-the-job instruction
Investigation
Study internal interactions of complex systems or subsystems
When Simulation is NOT appropriate
Problem solvable by common sense
Problem solvable analytically
Direct experiments are less expensive
Costs exceed potential savings
Resources or time are unavailable
Data or system estimates are missing
System behavior is too complex to define
Advantages and Disadvantages
Advantages
Explore new policies without disrupting operations
Test new hardware designs without acquisition
Time compression or expansion
Bottleneck analysis
What-if analysis
Disadvantages
Requires special training
Time consuming and expensive
Inappropriate use when analytical solutions exist
Results can be difficult to interpret
Areas of Application
Manufacturing and Wafer Fabrication
Business Process and Retail
Construction and Project Management
Logistics, Transportation and Distribution
Military and Health Care
Logistics Supply Chains Transportation
Relevant Case Studies
Subway Passenger Flow
Results
Proved inverse relationship: Higher density → walking speed drops to near-zero (0.2 m/s)
Identified specific choke points (e.g., B1MiddleOut)
Solution
Agent-Based Simulation using turnstile data to map density
Problem
Overcrowding and bottlenecks during peak transfers
Context
59th-Street Columbus Circle Transfer Station (NYC)
Disaster Relief Inventory
Result
Short replenishment cycles (5 days) are most effective
Frequent, smaller funding intervals reduce human suffering (deprivation costs) more than lump sums
Solution
Open-source Java Simulation Engine for inventory policy testing
Problem
Stochastic funding, demand uncertainty, and migration
Context
Refugee camps (Turkey/Syria) handling perishable meds and hygiene kits
Maritime Urban Logistics
Result
Longer system lifecycles yield higher emission savings
Cost-effective if truck-to-ship cost ratio exceeds 2:1
Solution
"PortalLite" (network of small, distributed ports) using waterways
Problem
Direct Trucking" causes high emissions and congestion
Context
Freight distribution in Chicago
Warehouse Staffing
Results
Allowed daily use by operations managers without simulation training
7% reduction in staffing while maintaining throughput
Solution
Cloud Simulation Platform (CSP) on AWS for non-experts
Problem
Spreadsheets failed to predict staffing needs; simulation was too complex for managers
Context
Amazon Inbound operations with complex freight mixes
Chemical Production Logistics
Results
Decreased hazardous employee interactions by ~25%
Reduced General Cargo Container usage by ~75%
Solution
Movable Tank Containers managed via Optimisation + Simulation
Problem
Stationary tanks are inflexible; manual handling is unsafe
Context
Shift to specialty chemicals requiring flexible storage