Intelligent Optimization: A Problem-Independent Solver for Real-World Problems

Optimization is the process of finding the best possible solution(s) for a given request. In practice, the space of potential solutions can be vast, requiring specific algorithms to effectively explore and determine the most suitable solutions. Typically, problems are approached individually, with separate considerations for problem modeling and algorithm design. However, this traditional approach can be impractical, time-consuming, and expensive, as it involves customizing the modeling and design for each specific problem. Hyper-heuristics (HHs) offer a different approach by providing problem-independent algorithmic components. Additionally, incorporating Machine Learning (ML) is crucial for developing general and robust optimization solvers. While this project is academically oriented, their aim is to incorporate new techniques to design a commercial product.