Monte Carlo Project Scheduler (mcps) is a command-line tool that runs Monte Carlo simulations on project schedules to estimate completion times and effort required. It helps project managers and engineers gain a better understanding of potential project risks and timelines by providing a probabilistic analysis of schedule durations and total work effort.

Features

Simulate Project Schedules: Run multiple simulations to estimate the probability distribution of project completion times and total work effort.
Customizable Inputs: Accepts project schedules in YAML or JSON formats, with options to override certain parameters like the number of workers or the number of iterations.
Visual Output: Generates an ASCII-based cumulative distribution function (CDF) graph, providing an easy-to-understand visualization of the simulation results.

Installation

Prerequisites

Rust: You'll need to have Rust installed on your system to build the project. You can install Rust using rustup:
```
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```

Building from Source

Clone and build the repository:

git clone <git@git.sr.ht>:~swaits/mcps
cd mcps
cargo build --release

The binary will be available at target/release/mcps.

Usage

Once you have built the tool, you can use it by providing a project schedule file in YAML or JSON format.

Basic Usage

./mcps example.yaml -i 100000 -w 10

This command runs the Monte Carlo simulation on the example.yaml schedule file with 100,000 iterations and overrides the number of workers to 10.

Command-Line Options

-i, --iterations <iterations>: Specify the number of iterations to run. Must be at least 100. Default is 50,000.
-w, --workers <num_workers>: Override the number of workers specified in the schedule file.
-v, --version: Print version information.
-h, --help: Print help information.

Schedule File Format

The tool accepts schedule files in YAML or JSON format. Below is an example of the YAML format:

num_workers: 5 # for the purpose of scheduling simulation
estimate_confidence: 0.80 # confidence actuals will fall inside estimate bounds
tasks:
  - id: DesignPhase
    min_time: 1.5 # 1.5 days
    max_time: 3.5 # 3.5 days
    dependencies: []
  - id: ImplementationPhase
    min_time: 2.25 # 2.25 days
    max_time: 4.75 # 4.75 days
    dependencies: [DesignPhase]

Example Output

The tool generates an ASCII-based cumulative distribution function (CDF) graph, which visually represents the distribution of project durations and effort:

Project Details

Contributing

Contributions are welcome! If you'd like to contribute, please fork the repository and make changes as you'd like. Pull requests are warmly welcomed.

Issues

If you encounter any issues with the tool, feel free to open an issue on the repository.

Acknowledgments

This tool was developed by Stephen Waits. Contributions and suggestions are always welcome!

License

This project is licensed under the MIT License. See the LICENSE file for details.