Inventory Management using Machine Learning

Implementation of four randomized Optimization algorithms in order to maximize profits given cost constraints.

Key Technical Insights:
• The Genetic Algorithm (GA) performed best, balancing exploration and exploitation to optimize inventory selection.
• Although MIMIC also provided high fitness values but because of its long runtimes, scalability of this model would've been an issue.

Business Impact:
• Enabled millions in increased sales through identification of the most in-demand product mix that fit the cost constrains
• Minimized losses from unsold inventory