Quantum Algorithms for Solving Multi-Constraint Optimization Problems

This project focuses on leveraging the power of quantum computing to address complex optimization problems that involve multiple constraints. Multi-constraint optimization problems are prevalent in various fields, such as logistics, finance, engineering, and machine learning, where solutions must satisfy several competing requirements simultaneously. Classical algorithms often struggle with the computational complexity of these problems, especially as the number of constraints and variables grows. Quantum computing, with its potential for exponential speedup in certain computations, offers a promising approach to solving such problems more efficiently. The project aims to develop and evaluate quantum algorithms tailored for multi-constraint optimization.

The project has the potential to significantly improve the speed and accuracy of solving complex optimization problems arising in real-work applications, enabling new applications and solutions in various industries. The project contributes to the growing body of research in quantum algorithms, offering innovative approaches that bridge the gap between theoretical quantum computing and practical optimization challenges.