balance_engine

Crates.iobalance_engine
lib.rsbalance_engine
version0.0.3-rc1
created_at2025-04-16 02:12:41.525874+00
updated_at2025-04-17 01:52:30.894655+00
descriptionProduction planning and optimization engine using linear programming to balance supply with demand while minimizing costs and respecting resource constraints
homepage
repositoryhttps://github.com/Yrrrrrf/balance_engine
max_upload_size
id1635563
size41,079
Fernando Bryan Reza Campos (Yrrrrrf)

documentation

README

Balance Engine Optimization Icon
Balance Engine

GitHub License: MIT PyPI version Crates.io Crates.io Downloads

A Python/Rust module for production planning and optimization using linear programming.

Balance Engine automates calculations to balance production with demand, allowing for precise and efficient planning while reducing costs. It uses linear programming modeling to optimize resource allocation in limited production cycles.

The tool handles key production variables including:

  • Yielded Supply
  • On Hand (Finished Goods)
  • Safety Stock Targets
  • Sellable Supply
  • Effective Demand
  • Total Projected Inventory Balance

Installation

Python Package

pip install balance-engine

Rust Crate

cargo add balance_engine

Features

  • Hybrid Architecture: Core optimization in Rust for performance, Python API for flexibility
  • Production Planning: Balance supply with demand while respecting capacity constraints
  • Inventory Management: Calculate optimal inventory levels that meet safety stock requirements
  • Resource Allocation: Efficiently allocate limited resources in production cycles

Project Structure

  • Rust Core: High-performance linear programming solver
  • Python Interface: Easy-to-use API for integration with data analysis workflows
  • Example Code: Sample implementations for common production planning scenarios

Usage

import engine

# Initialize the engine
engine.init()

# Use the optimization functions
result = engine.optimize_production_plan(
    products=["ProductA", "ProductB"],
    demand_dict={"ProductA": 100, "ProductB": 150},
    production_rates_dict={"ProductA": 10, "ProductB": 15},
    available_hours=20,
    current_inventory_dict={"ProductA": 20, "ProductB": 10},
    min_inventory_dict={"ProductA": 10, "ProductB": 20}
)

print(result)

License

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

Commit count: 20

cargo fmt