Time minimization of warehouse work shift

Supply Chain Process Design using the Queueing Theory

Warehouse Optimizer is a web-based tool designed to streamline warehouse operations by optimizing product placements based on customer orders. It enables warehouse managers to upload warehouse maps, manage product storage, and analyze order data to enhance efficiency.

Warehouse path optimization using Reinforcement Learning (RL) enables agents to learn efficient routes by interacting with the environment. The system improves over time by minimizing travel distance and adapting to dynamic warehouse conditions, leading to smarter and faster logistics operations.

This project helps reduce walking time in warehouses using a Python tool that simulates picking routes. Users can test strategies like wave picking and clustering on a 2D layout to find the most efficient method.

My Bachelor's final project

A project showcasing a scheduling algorithm to optimize warehouse robot coordination for efficient product delivery and order fulfillment.

A gravity-aware 3D spatial packing system that places multiple cuboid items inside a fixed container using deterministic heuristics. It sorts items, checks collisions, enforces support under gravity, computes valid (x,y,z) positions, validates constraints, and visualizes final stacking for correctness in a clear, stepwise pipeline.

LogiTrack is a Python & Streamlit-powered inventory management system for real-time warehouse optimization. It offers multi-warehouse planning, interactive maps, and supply chain analytics, supporting global coordinates, CSV/SQL data, and customizable parameters.

Predictive optimization model designed to improve logistics efficiency for Lavazza by identifying cost-effective warehouse locations and distribution strategies, ultimately saving 15% on transportation costs.

AI-Enhanced Supply Chain Optimization (AIESCO) is an AI-based algorithm designed to optimize supply chain operations and logistics.

Three Wheel Holonomic Drive for Warehouse Automation Capstone Project, made by final year students at MITWPU '23.

Robotic goods-to-person warehouse picking simulation with throughput analysis

Student research: Multi-robot warehouse optimization (Simulation & Physical prototype)

Reinforcement learning simulation for warehouse workforce optimization. PPO agent learns worker assignments, order flow, and shift logistics across seasonal demand cycles. Foundation for Jack.

Slotting simulation stochastic demand

PPO + LSTM reinforcement learning agent with temporal memory for warehouse workforce optimization. 261 simulated days, 7 workers, 98.2% order completion across ~9.4 years of training.

ML-driven warehouse slotting optimization using order frequency patterns

Product affinity co-location analysis

Warehouse slotting optimizer — De Koster et al. methodology