VN2 Inventory Planning Challenge
Share:
Finished
competition-bg

VN2 Inventory Planning Challenge

Test your inventory planning skills: cut holding costs, prevent shortages, and master real-world inventory planning.

DataSource.AI
E-commerce/Retail
Total Prize 18,000
Scroll To Top

Ph D · 29 September 2025

563
Copied!
2

UPDATED// Starter Notebook // Model‑Based Ordering with Per‑SKU Routing (SES/Croston/TBATS) + Base‑Stock Submission

A production‑ready notebook that routes each SKU to SES, Croston, or TBATS based on data features, estimates μ̂ and σ̂ per SKU, and generates a valid base‑stock submission CSV in the platform’s index order. Repo: http://github.com/senoni-research/vn2inventory.

Description

This notebook is designed for quick, high‑quality submissions in VN2. It prioritizes actionability over demo:

 

Feature-driven routing

  • Computes per‑SKU features: mean demand, zero fraction (intermittency), STL seasonal strength (period=52), and series length.
  • Routing rules:
  1. Intermittent (zeros high, mean low) → Croston‑SBA
  2. Seasonal (high seasonal strength, sufficient length) → TBATS
  3. Otherwise → SES
  • Per‑SKU demand and uncertainty
  1. Estimates μ̂ from short‑horizon forecasts (or series mean for Croston).
  2. Estimates σ̂ from residuals (fallback to series std when needed).
  • Base‑stock policy and submission
  1. Uses protection period P=3 (lead 2 + review 1).
  2. Computes orders from demand_stats_modelled and current state built from Initial State (on_hand = End Inventory, on_order = W+1 + W+2).
  3. Writes submissions/orders_round1_advanced_modelled.csv with the exact platform index order.
  • Clean outputs and inline docs
  1. Inline markdown before each step explains the logic; warnings are suppressed to keep outputs readable.

How to use

  • Run top‑to‑bottom; the last cell prints the path to the generated CSV.
  • Modify routing thresholds (ZERO_FRAC_THR, LOW_MEAN_THR, SEASON_STRENGTH_THR, MIN_LEN_TBATS) to fit your portfolio.
  • Repository: http://github.com/senoni-research/vn2inventory.

 

      
      
    

Comments

Join our private community in Discord

Keep up to date by participating in our global community of data scientists and AI enthusiasts. We discuss the latest developments in data science competitions, new techniques for solving complex challenges, AI and machine learning models, and much more!