monte-carlo-simulation

What problem does it solve?

Monte Carlo simulation provides a structured method to quantify uncertainty in costs, schedules, revenues, or other targets by sampling from user-supplied distributions and aggregating results.

Core Features & Use Cases

• Supports distributions including triangular, normal, uniform, PERT, and discrete; runs 10,000 iterations by default; outputs percentiles (P10, P50, P80, P90, P95); computes probability of meeting a target; provides a sensitivity tornado; offers contingency recommendations; supports Mermaid diagrams with optional PNG export.
• Use cases include project cost and schedule risk assessment, revenue forecasting under uncertainty, and contingency planning for high-stakes commitments.

Quick Start

Provide a model specification with variables and distributions and a target formula to run a Monte Carlo simulation.