Optimization Made Easy with Low-Code: Solve Real-World Problems Without Heavy Coding

Table of Contents

Optimization Made Easy with Low-Code: Solve Real-World Problems Without Heavy Coding

 Why do we do optimization

 Challenges

 Proposed Solution

 User Story

 Requirements for Solving Optimization Problems

 Demo

Why do we do optimization

• Make better decision
• Reduce costs
• Improve performance
• Maximize efficiency

Challenges

• Involve complex mathematics
• Require extensive programming

Proposed Solution

• Low-code approach that can solve wide range of optimization problems with minimal coding

User Story

Green Tiger Mobility Innovates Battery Management System Challenge - Limited expertise in developing high-quality e-mobility products - Difficulty in optimizing battery management systems Solution - Optimize battery pack performance with Live Task - Utilize MATLAB including Live Script to document the analysis Result Successful completion of the BMS project with an impressive mileage of 70 kilometers (43.5 miles) on a 1.8 kWh battery

Requirements for Solving Optimization Problems

1. Variables
2. Goal - maximization or minimization
3. Objective function
4. Constraints

Demo

Run this below in command window:

edit Demo.mlx