cumcm-b - Optimization methods for CUMCM B problems
Models CUMCM B problems involving optimization, operations research, planning, uncertainty, networks, queuing, and sensitivity analysis.
Tags
Updated: 2026-09-30mathematical modelingoperations researchoptimizationlinear programminginteger programmingdynamic programmingheuristic algorithmsMonte Carlo simulationnetwork optimizationqueuing theory
Capabilities
Typical Inputs
What this skill does
- Define decision variables
- Construct objective functions
- Translate constraints
- Classify optimization models
- Select solution algorithms
- Perform sensitivity analysis
- Run Monte Carlo simulations
- Model network problems
- Analyze queuing systems
Inputs
- Problem statement
- Decision requirements
- Resource limits
- Demand data
- Cost parameters
- Probability distributions
- Network data
- Model parameters
Outputs
- Optimization model
- Decision variable values
- Optimal or candidate solution
- Sensitivity analysis
- Simulation statistics
- Network solution
- Queuing metrics
- Executable Python code
Requirements
- Python environment
- NumPy support
- SciPy support
- Optional PuLP package
- Optional NetworkX package
- Optimization solver support