Machine Learning-Based Vehicle Assignment Model for Dispatch Operations

Description

Code 1 develops and validates the Random Forest model for vehicle assignment, including data preparation, model training, performance metrics, and professional visualizations comparing the AS IS and TO BE dispatch times. Code 2 builds the supervisor interface, integrating ERP/WMS inputs, RFID/IoT traceability, vehicle availability, priority queue management, feasible transport alternatives, cost validation, and decision history to support faster, traceable, and data-driven dispatch decisions.

Steps to reproduce

1. Run Code 1 to train and save the Random Forest model. 2. Run Code 2 to launch the supervisor interface. 3. Click Cargar pedidos desde ERP/WMS. 4. Select or load a prioritized order. 5. Click Evaluar pedido and review the vehicle recommendation.

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