Optimization Toolkit

Optimization Toolkit is a Python script designed to facilitate multi-objective optimization in engineering applications. It offers a flexible framework to optimize systems while considering technical, economic, and environmental factors. By leveraging the SciPy library, this toolkit provides efficient optimization algorithms, ensuring robust solutions that meet diverse requirements.

Key Features

• Multi-objective Optimization: Incorporate multiple objectives, such as technical performance, cost, and environmental impact, into the optimization process.

• Constraint Handling: Define constraints on variables to ensure feasibility in real-world engineering problems.

• Customizable Weights: Assign weights to each objective to reflect their relative importance in the optimization process.

• Interactive Interface: User-friendly text-based interface guides users through inputting weights, initial variable values, and displays optimization results.

Usage

1. Installation: Ensure you have Python 3.x installed along with the required dependencies listed in requirements.txt. You can install the dependencies using pip:

   pip install -r requirements.txt

2. Running the Script: Run the optimization.py script:

   python optimization.py

3. Input Parameters: Follow the prompts to provide weights for each category (technical, economic, environmental) and initial variable values.

4. Optimization Results: The script will perform optimization and display the optimal variable values along with the minimum function value.

Example

Here's a simple example demonstrating how to use the Optimization Toolkit:

$ python optimization.py

Enter weights for each category (technical, economic, environmental): Technical: 0.4 Economic: 0.3 Environmental: 0.3 Enter initial variable values: Variable 1: 2 Variable 2: 3

Optimal variable values: [1.5 8. ] Minimum function value: 25.0