Python library for Applied Computational Supply Chain & Logistics. Unlock Neural Nets, Bayesian EOQ, Optimization, Time Series, and more for smarter decisions.

This project provides comprehensive solutions for vehicle routing, delivery scheduling, and optimization in logistics operations.

3D bin packing is a classical and challenging combinatorial optimization problem in logistics and production systems. An effective bin packing algorithm means the reduction of total packing cost and increase in utilization of resources. Because the cost of packing materials, which is mainly determined by their surface area, occupies the most part of packing cost, and in many real business scenarios there is no bin with fixed size, so AI Department of Cainiao proposed a new type of 3D bin packing problem. The objective of this new type of 3D bin packing problem is to pack all items into a bin with minimized surface area. And a DRL method based on the sequence-to-sequence model is proposed to solve the problem. This is the research paper link: https://arxiv.org/abs/1708.05930. Source code of this method can be found in the project.

Logistics Management System: An android application to manage an optimized solution for local logistics and transportation needs for both businesses and consumers in the urban areas.

The quantum supply chain manager is a quantum solution for logistics problems. We use the power of quantum machine learning for product [backorder](https://www.investopedia.com/terms/b/backorder.asp) prediction and quantum optimization for finding the best route to pick those products with high demand to store them in strategic warehouses. With the first technique, our clients can be prepared for increasing the production of their products when they are in high demand. Once we have established a set of products needed during a period of time, we use our second solution, the vehicle routing problem (VRP) solution to find the optimal route for picking these products. This reduces considerably costs associated with logistics, transportation, backorders, and overstocking for our clients. In summary, these solutions will improve business in terms of client satisfaction, backorder and shipping transportation costs.

- A repository for applying ML to optimize supply chain management, covering demand forecasting, inventory, logistics, and supplier selection. Includes Jupyter notebooks, Python scripts, and datasets for real-world applications.

The supply chain dataset presents a comprehensive set of information related to product sales, manufacturing, and logistics. The challenge is to extract meaningful insights and actionable recommendations from the data to optimize supply chain operations and improve profitability.

卡车-无人机协同配送系统，通过多智能体强化学习(MAPPO)算法优化物流配送效率。系统模拟真实的城市配送场景，其中卡车作为移动补给站，无人机执行最后一公里配送任务。optimized using Multi-Agent Reinforcement Learning (MAPPO) algorithms to enhance logistics delivery efficiency. The system simulates real-world urban delivery scenarios where trucks serve as mobile supply stations, and drones carry out the last-mile delivery tasks

Revolutionize supply chain of your company with the project—predict demand, optimize inventory, and streamline routes using data analysis and machine learning. Stay ahead, reduce costs, and embrace sustainable, efficient logistics. The future of supply chain management starts here.

Quick reference guide with useful information gathered by researchers of the Logistics and Optimization Group of the Universidade Federal da Paraíba (LOG-UFPB).

In accordance with survey reports, the growth of online business worldwide is significantly faster and higher in comparison with traditional businesses. The achievements of online commerce has been so impacting that even established business houses have started out online promoting as a complementary work. However, first things always come first, and in case of internet commerce, it is mandatory to create an eCommerce website at the outset. There is a definite way of practicing the process of creating and operating an internet commerce website. Though a professional involvement is always solicited for such efforts, a good knowledge could also help in initiating an online business. Follow these steps to create your eCommerce store from Scratch: Decide the Merchandise You Want to Offer While browsing the internet you'll want noticed the presence of multiple eCommerce websites selling varied items. There are certain websites dedicated to selling a particular line of products or software program as garments, travel plans, fashion items, and so forth. Also, there are some other eCommerce websites that sell multiple things like mobile phones, laptops, household appliances, books, CDs, home cinemas, helpful cams, sports goods, and so on. The particular latter is a like a huge departmental store selling everything under the same roof. At the outset, it is thus important to decide on the merchandise or service that you would like to offer through your website. While selecting the item of trade you will need to estimate the local demand. Purchasers would always prefer to be able to buy items from a local vendor irrespective regarding being online or traditional. Typically the local supplier would always ensure faster deliveries, easier payment terms, and previously replacements in case of wrong or defective deliveries. Choose Your Business Type As an eCommerce business owner, you can choose your business design as each your requirement. Either you can sell only throughout your online store, or, can sell your products on marketplaces like Amazon, FlipKart, eBay, and so forth You can also sell your products on both the programs each time. Choose a Company and Domain Once you have decided on your array of items and business model, the next step would be to choose a business name and create a domain. A business name should be relevant to your products and easy to remember for your target audience. A website gives an identity and makes it easier for online buyers to recognize you. However, for companies with limited financial resources, it would be desirable to get a shared domain. Sharing a domain with an established name makes it easier for calling your target customers. Because the business grows it would be smart to have a dedicated domain as it helps in lookup engine optimization and easier recognition. Select an e-commerce Website Constructor Nowadays, it is very simple to build your online store by using eCommerce website builders like KartRocket. These kinds of DIY online software create websites in few secs to can start promoting products instantly. Designing Your own eCommerce Store Your eCommerce website is your store, and it needs to be made for the convenience of your buyers. Because in a store, your website should contain details about your saleable products and services. Images, explanations, prices, users’ comments, scores should all be as part of your web page for helping prospective buyers. You must make it certain, that your web page displays your products perfectly so that buyers are never misled. You need to make your web pages and website attractive as that will be your representation to buyers online. Set Up the Repayment Entrance As an online business, one must have multiple payment options available for the customers. The eStore builders like KartRocket come with tools that can set up these benefits to your website automatically. The customer should be able to make payments via credit card, debit credit card, online wallets, net bank, COD, etc. Secure Your Website by Installing SSL Certificate For the websites that transfer data online, one must make sure that their connection is protected by a secured security layer (SSL). The SSL document keeps your website secure and builds the trust among your customers. Today, even Google recommends having an SSL certificate for every single website. Select Your own Shipping Partner Once you start selling products through your eCommerce website, you will need to ship those products to your customers with the aid of courier services. eCommerce logistics aggregator services like ShipRocket are the best option to go for. They give you multiple courier organization options to ship your product with the least expensive available shipping charges, so you might have maximum income value in your reveal. These are the basic steps in creating an eCommerce website for your product or service and commence marketing instantly.

Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Genetic Algorithm

This project aims to optimize logistics processes using Artificial Intelligence (AI) techniques. By leveraging AI algorithms and data analytics, the project seeks to enhance efficiency and reduce costs in supply chain management, inventory management, route optimization, and demand forecasting.

I analyzed retail data (2022–2023) using Python (ETL) and SQL. Identified top products, regional trends, and sales growth, providing actionable insights to optimize logistics, boost sales, and improve profitability.

The Packing problem has gained much relevance with the recent upheaval of the delivery and retail industry. Companies all over the world are now subject to massive logistics & operations schemes, and their warehouses‘ e ectiveness is irrevocably bound to how well their products are packed into trucks for distribution. Optimizing this process may lead to huge improvements in performance, time use, resource management and to ultimately increasing profits. Seeking to perform and deliver this optimization, this work proposes a new method called “Deep Box Packing” (DBP), an online system which is able to provide an optimized packing strategy for an arbitrary set of three-dimensional boxes arriving in real-time. DBP was trained using Deep Reinforcement Learning and leverages the power of attention mechanisms in a modified version of the Transformer Network called here the Mapping Transformer. It was conceived to work under partial information, in real-time, and to respond to all of the three inherent questions of packing: which box to take (selection), where to place it in the container (position) and how to place it (orientation) at every given moment in time. Its reward function was tailored not only in terms of optimizing the final Volume utilization of the container but also in terms of the feasibility of the packing sequence, withholding constraints such as box stability and accessibility to the packing positions from the entrance of the container. Under this scenario, DBP was capable of achieving outstanding results in the tested instances up to 100% volume utilization in fully feasible packings. Under comparative tests, DBP considerably improved results obtained from a wall-building LB-Greedy heuristic and showed high generalization capacity to different sizes of the Information window (number of boxes from the whole sequence it can see and choose from at any moment in time). After a set of visual step-by-step analyses of DBP’s behavior in generated packing sequences, it was also shown that it was able to achieve high geometric understanding and great potential for being expanded into a real warehouse scenario.

Vehicle Routing Optimizer is a Python project that solves the Vehicle Routing Problem using Google OR-Tools and Open Route Service API. It can handle different VRP variants and generate GeoJSON paths that could be used to visualize and compare solutions. It is a useful tool for logistics and transportation optimization.

this project showcases the successful development of an autonomous robotic forklift system, highlighting its potential impact on enhancing warehouse efficiency and optimizing material handling operations. The insights gained from this project contribute to the advancement of robotics technology in the field of logistics and automation.

in order to solve the optimization problem of logistics distribution system for fresh food, it provides a low‐carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low‐carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model.

Vehicle routing problem (VRP) is a generic name referring to optimization problems in transportation, distribution and logistics industry. Route planning techniques is one of the main tasks of VRP which aims to find an optimal route from a starting point to a destination on a road map. Choosing an appropriate route planning algorithm among the existing algorithms in the literature to apply it in real road networks is an important task for any transportation application. In this project, we first present two of the different route planning algorithms, and then explain how we compare and analyze their performance when they are applied in real road networks.

Hashing, searching, sorting, tree algorithms, dynamic programming, greedy algorithms, divide and conquer, random number generation, and randomized algorithms are examples of algorithms students learn to exploit to solve problems ranging from logistics and route optimization to DNA sequencing.

It can be described as the combination of vehiclerouting and inventory management problems, in which a supplier has to deliver products to a number of geographically dispersed customers, subject to side constraints. It provides integrated logistics solutions by simultaneously optimizing inventory management, vehicle routing, and delivery scheduling. Some exact algorithms and several powerful metaheuristic and matheuristic approaches have been developed for this class of problems, especially in recent years. The purpose of this article is to provide a comprehensive review of this literature, based on a new classification of the problem. We categorize IRPs with respect to their structural variants and the availability of information on customer demand.

RELOG: Reverse Logistics Optimization

The dashboard delivers valuable insights into distribution logistics, enabling automotive companies to optimize their supply chain operations, reduce costs, and enhance overall efficiency.

EcoSync is a waste management system for Dhaka North City Corporation, built with Express.js and React. Developed for Code Samurai 2024, it optimizes waste collection, transportation, and processing through innovative technology, EcoSync effectively streamlines urban waste logistics.

proDuck-WMS (Warehouse Management System) is a full-stack warehouse management application built with the MERN stack (MongoDB, Express.js, React, and Node.js) to streamline inventory control, optimize workflow efficiency, and manage logistics processes in real-time

This project implements a solution for optimizing delivery routes using Deep Q-Networks (DQN), a reinforcement learning approach. The system can adapt to dynamic traffic conditions, making it valuable for real-world logistics applications.

Robotics and Automation have played a major role in the field of automobile manufacturing, space research, logistics, agriculture and many more. One such robot is a welding robot which is programmed to weld a product in the automotive industry. These robots are very accurate and don’t have any errors. But, sometimes due to some vibrations in the motors or due to any external factors, the robot may deviate from its specified position which leads to defective welding of a product. The robot arm is subjected to object tracking. The position of the robot arm is tracked by mounting an accelerometer on the robot arm. This position deviation can be corrected by using Kalman filtering technique. Kalman filters are used in the field of robotics motion planning, control and trajectory optimization. A com-mon application is for state prediction and estimation, object tracking. This paper is about applying Kalman filtering technique to a three-axis accelerometer which is mounted on the robotic arm of a welding robot. The voltage values of the accelerometer sensor are taken for state prediction and by recursive iterations the values are optimized such that error becomes minimum when the robot has deviated from its desired position.

Python codes for logistics optimization problems

⚓ Abyssinia Maritime – A Java console app for cargo logistics, vessel tracking, and port management. Includes Rust for route/ETA optimization, Python for cost automation, and Node.js for reporting. Simulates real-world maritime logistics and supply chain operations.

SeraySis is a custom-built Customer Relationship Management (CRM) system originally developed in 2018 for Seraytrans, a logistics company. This .NET-based application was designed to streamline operations, enhance customer service, and optimize resource management specifically for the needs of Seraytrans and the broader logistics industry.