retailscm-biz-suite - 供应链，零售供应链中台系统，集成零售管理, 电子商务, 供应链管理, 财务管理, 车队管理, 仓库管理, 人员管理, 产品管理, 订单管理, 会员管理, 连锁店管理, 加盟管理, 前端React/Ant Design, 后端Java Spring+自有开源框架，通过REST接口调用，前后端完全分离。

•    Java

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供应链，零售供应链中台系统，集成零售管理, 电子商务, 供应链管理, 财务管理, 车队管理, 仓库管理, 人员管理, 产品管理, 订单管理, 会员管理, 连锁店管理, 加盟管理, 前端React/Ant Design, 后端Java Spring+自有开源框架，通过REST接口调用，前后端完全分离。

retail erp scm antd redis spring arangodb mysql tms fleet-management warehouse-management training-module ordermanagement ecommerce oracle-atg-alternative accounting-tools digital-transformation echarts knowledge-graph

Hammond - Self hosted vehicle management system to track fuel and other expenses related to all of your vehicles

•    Go

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Hammond is a self hosted vehicle management system to track fuel and other expenses related to all of your vehicles. It supports multiple users sharing multiple vehicles. It is the logical successor to Clarkson which has not been updated for quite some time now.

vehicle-management fleet-management expense-tracking vehicle-expense-tracking fuel-expense

Bing-Maps-Fleet-Tracker - The Bing Maps Fleet Tracker is a tracking solution for small to medium sized teams

•    CSharp

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Bing Maps Fleet Tracker is a fleet management solution based on the Bing Maps APIs. It offers functionalities that enable tracking and managing a fleet of vehicles in real time. For more details, read this blog post. To get this project up and running, the easiest way is to use the Bing Maps Fleet Tracker Deployment Portal, which one-click deploy the Bing Maps Fleet Tracker solution into your Azure subscription. For a step by step walkthrough of how to deploy use the deployment portal, see out of the box deployment. None of the data entered on the deployment portal is stored by Bing Maps Fleet Tracker. It is only used to configure your deployment.

bing-maps gis fleet-management logistics

simobility - simobility - light-weight mobility simulation framework. Best for quick prototyping

•    Python

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simobility is a human-friendly Python framework that helps scientists and engineers to prototype and compare fleet optimization algorithms (autonomous and human-driven vehicles). It provides a set of building blocks that can be used to design different simulation scenarious, run simulations and calculate metrics. It is easy to plug in custom demand models, customer behavior models, fleet types, spatio-temporal models (for example, use OSRM for routing vehicles and machine learning models trained on historical data to predict ETA). Create an environment for experiments with machine learning algorithms for decision-making problems in mobility services and compare them to classical solutions.

simulator transportation ridesharing simulation-framework autonomous-vehicles mobility fleet-management optimization-algorithms mobility-modeling ridehailing