Supply Chain Process Design using the Queueing Theory
Time minimization of warehouse work shift
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.
A project showcasing a scheduling algorithm to optimize warehouse robot coordination for efficient product delivery and order fulfillment.
Procedural KTY Generator creates export-ready cardboard container models through the Blender Python API. The generator produces configurable KTY boxes with different quality levels, open/closed/damaged states, procedural materials, metadata export, .blend files and preview renders
Supply-chain and logistics modeling for Konjugate: ports, warehouses, road and rail lanes conserving containers and trucks as stocks and flows, plus a toolbox that turns any region's OpenStreetMap data into a runnable network model.
When Not to Reconfigure: Sequential Expert Routing for Dynamic Warehouse Slotting under Non-Stationary Demand
Top Warehouse Slotting Optimization 🌟 Star if you like it! 🌟
Student research: Multi-robot warehouse optimization (Simulation & Physical prototype)
Optimizing warehouse robot navigation on a 10×10 grid using Q-Learning with epsilon-greedy exploration and the Bellman equation
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.
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.
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
Swift Logistics Warehouse Bottleneck Assessment
An AI agent that plans a warehouse's day: it forecasts demand, finds the SKUs in demand, plans replenishment from levels 3-4 to 1-2 and sets workers per day, on a live dashboard.
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