Case Studies
Case Studies
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Ahsan Khan – Case Studies in Operations Research
Ahsan Khan – Case Studies in Operations Research
Operations Research Analyst | Master’s in Mathematics | Problem Solver across Industries
Introduction
Introduction
As an Operations Research Analyst, I, Ahsan Khan, specialize in converting complex operational problems into actionable, mathematical solutions. With a Master’s degree in Mathematics and a deep understanding of modeling, optimization, and analytics, I’ve helped businesses, hospitals, and public services in Pakistan make smarter decisions backed by data.
Here are a few real-world case studies from my portfolio that demonstrate the power of Operations Research in action.
CASE STUDY 1: Cutting Transportation Costs for a Textile Manufacturer
CASE STUDY 1: Cutting Transportation Costs for a Textile Manufacturer
Client: Leading Textile Company, Faisalabad
Problem: High logistics and transportation costs; inefficient routing across factories and warehouses.
Solution:
Solution:
Designed a transportation and assignment model using Linear Programming.
Used Excel Solver and Python (PuLP) for computation and scenario testing.
Applied cost minimization constraints and solved for optimal routing.
Results:
Results:
25% reduction in overall shipping costs.
Streamlined warehouse-to-retailer dispatch system.
Real-time dashboard built in Power BI for continuous tracking.
CASE STUDY 2: Optimizing Hospital Emergency Room During COVID-19
CASE STUDY 2: Optimizing Hospital Emergency Room During COVID-19
Client: Public Sector Hospital, Lahore
Problem: Long wait times in ER, limited ICU beds, poor patient flow during pandemic.
Solution:
Solution:
Created a queueing model to simulate patient flow.
Implemented discrete-event simulation using Arena.
Forecasted demand with statistical modeling and added real-time bed tracking.
Results:
Results:
ER wait times reduced by 40%.
ICU usage optimized by over 30%.
Daily decision-making improved through a simple forecasting dashboard.
CASE STUDY 3: Bus Network Optimization in Islamabad
CASE STUDY 3: Bus Network Optimization in Islamabad
Client: City Transport Department, Karachi
Problem: Overcrowded routes, low service reliability, inefficient fleet allocation.
Solution:
Solution:
Developed a network optimization model using Integer Programming.
Conducted a passenger flow analysis and modeled peak-hour demands.
Proposed a route rebalancing strategy using Graph Theory.
Results:
Results:
Reduced average commute time by 20%.
Improved fleet efficiency and route coverage.
Public satisfaction score increased in surveys post-implementation.
CASE STUDY 4: Employee Scheduling for a Manufacturing Plant
CASE STUDY 4: Employee Scheduling for a Manufacturing Plant
Client: Steel Manufacturing Unit, Sialkot
Problem: Unbalanced shifts, excessive overtime, worker dissatisfaction.
Solution:
Solution:
Built a shift scheduling model using constraints on skill, availability, and labor laws.
Used Gurobi with Python for precise optimization.
Balanced workload based on forecasted production needs.
Results:
Results:
Overtime reduced by 35%.
Increased on-time production rates.
Fairer shift distribution improved worker morale.
CASE STUDY 5: Inventory Forecasting for an E-commerce Startup
CASE STUDY 5: Inventory Forecasting for an E-commerce Startup
Client: Online Retail Startup, Islamabad
Problem: Frequent stockouts, excessive storage costs, inaccurate demand prediction.
Solution:
Solution:
Created a time-series forecasting model using Python and Excel.
Implemented safety stock calculation using probabilistic models.
Built a reorder point system integrated into inventory software.
Results:
Results:
Stock availability improved by 25%.
Inventory costs reduced by 18%.
Helped scale operations with confidence in demand planning.
My Approach
My Approach
For every project, I follow a structured Operations Research workflow:
Define the problem clearly.
Build a mathematical model.
Use the right tools (Solver, Python, LINGO, Arena, etc.).
Test multiple scenarios.
Implement and monitor impact.
Tools & Techniques Used
Tools & Techniques Used
Modeling: Linear/Integer Programming, Network Models, Queueing Theory
Software: Excel Solver, Python (PuLP, NumPy, Gurobi), Arena, Power BI
Domains: Manufacturing, Healthcare, Transport, Retail, Public Sector
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