Columbia’s M.S. in Operations Research empowers students to design, analyze, and implement models that enhance efficiency and decision-making in logistics, finance, healthcare, and technology. These topics span stochastic processes, simulation, linear programming, and modern analytics.
Optimization of Last-Mile Delivery Using Vehicle Routing Algorithms
Simulation of Emergency Department Queues for Resource Planning
Multi-Objective Supply Chain Network Design with Cost and Emissions
Inventory Optimization for Seasonal Retail Products
Stochastic Programming Model for Portfolio Allocation
Simulation-Based Optimization of Airport Gate Assignments
Game-Theoretic Approach to Competitive Pricing in E-Commerce
Heuristic Methods for Nurse Scheduling in Large Hospitals
Dynamic Programming for Maintenance Planning in Manufacturing
Linear Programming for Classroom Allocation Optimization
Risk-Aware Logistics Planning Using Robust Optimization
Forecasting Energy Demand with Time-Series and Machine Learning
Data-Driven Ride-Sharing Optimization Using Mixed-Integer Programming
Operations Planning Model for Food Distribution in Urban Slums
Predictive Maintenance Modeling Using Failure Time Distributions
Air Traffic Flow Management Using Network Flow Algorithms
Customer Service Simulation for Staffing Decisions in Call Centers
Transportation Mode Choice Modeling with Discrete Choice Analysis
Warehouse Layout Optimization for Order Picking Efficiency
Decision Tree Framework for Loan Approval Optimization
Collexa supports operations research students with solver tools like Gurobi, CPLEX, Arena, and Python-based model building, plus data cleaning and simulation reports.
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