נושא הפרוייקט
מספר פרוייקט
מחלקה
שמות סטודנטים
אימייל
שמות מנחים
אופטימיזציה במחסנים חכמים
Smart Warehouse Optimization
תקציר בעיברית
תקציר באנגלית
In our project we extend a task allocation simulator originally developed for Law Enforcement Problems to address Smart Warehouse Problems. Our project demonstrates the simulator's versatility and effectiveness in optimizing task assignments in a warehouse environment. Through experimentation and proof-of-concept development, we show how the simulator efficiently allocates tasks among robots, including picking, packing, restocking, and maintenance. Our findings highlight the simulator's potential as a valuable tool for enhancing task allocation processes in various operational settings. This project focuses on developing a smart warehouse simulator to solve task allocation problems. We first define the problem verbally and mathematically, followed by creating an event-driven scheme that represents the flow of events in the simulator. Based on this scheme, we implement the simulator, which incorporates three different algorithms: greedy, a more sophisticated algorithm developed by us, and the Hungarian algorithm. Each algorithm provides a score based on our defined Key Performance Indicators (KPIs) such as Soft-Deadline and Task-Importance. The methodology encompasses both the research process in defining the problem and the development process in building the simulator. Through our experiments, we compare the performance of the different algorithms in solving the task allocation problem within the smart warehouse context. The deliverables of this project consist of a functional simulator designed for smart warehouses, with the capability to be adapted to various types of warehouses utilizing different robot systems and Key Performance Indicators (KPIs). The developed simulator provides users with analytical results for each algorithm employed, allowing for customized analysis based on user-defined input scenarios. This comprehensive tool enables customers to evaluate and optimize task allocation strategies within their warehouse operations. The versatility and adaptability of the simulator offer practical solutions for enhancing efficiency and decision-making in different warehouse environments. The main accomplishments of this project include extending an abstract simulator to address the smart warehouse problem with customized adaptations. This showcases the simulator's versatility and the ability to solve various problems beyond its initial focus on law enforcement. By implementing three different task allocation algorithms and providing analysis results based on user-defined scenarios, the project offers valuable insights for designing optimized task allocation strategies in diverse warehouse environments.