This project presents a practical implementation of a Genetic Algorithm (GA) for optimizing the GPD (Gross Profit Difference) of a company based on historical financial data. The algorithm aims to discover better configurations for critical business parameters such as:

• Number of Employees
• Marketing Budget
• Revenue
• Expenses

By combining financial data from two months and applying controlled mutations, the algorithm evolves towards more optimal configurations that improve the company's GPD.

• ASP.NET Core MVC 8.0
• Entity Framework Core
• C# (Genetic Algorithm implementation)
• Chart.js (for visual representation)
• JavaScript/HTML/CSS (for interactivity and UI)

• GeneticService.cs: Core class that implements the genetic algorithm logic, including population combination, mutation, and selection.
• FinancialController.cs: ASP.NET controller that loads financial data from the database and feeds it into the optimizer.
• Index.cshtml: Razor view that displays GPD comparison charts and interactive tables.

1. Initial Population
   Two historical financial entries (representing different months) are selected as the base generation.

2. Combination & Crossover
   A new candidate is created by averaging the values of the two parents.

3. Mutation Phase
   Key parameters such as Revenue, Expenses, MarketingBudget, and EmployeeCount are randomly mutated within predefined bounds.

4. Domain-Specific Constraints

   • Ideal employee count: 15
   • Acceptable range: 5 to 20
   • Marketing budget range: 100,000 to 700,000
   • Revenue-to-expense ratio must remain within a realistic range (e.g., 1 to 5)

5. Fitness Evaluation GPD is used as the fitness function. If a mutated candidate has a higher GPD, it replaces the current best.

6. Optimization Cycle The mutation and evaluation process is repeated for 100 generations, ensuring convergence toward an optimal solution.

An interactive line chart is displayed comparing the Actual GPD with the Optimized GPD over time.

• 🟦 Blue Line: Real data
• 🟩 Green Dashed Line: Optimized results

• Click on any chart point to view a detailed comparison table showing the actual vs. optimized values for:

  • Revenue
  • Expenses
  • Employee Count
  • Marketing Budget
  • GPD

• Color-coded values in the comparison table indicate improvement (green) or decline (red).

This project is for educational purposes and is shared publicly on GitHub. You are welcome to fork and adapt it for learning, research, or personal use.