"METSlib进化算法框架：现代化C语言下的元启发式算法库"

COIN-OR METSlib is a powerful metaheuristics framework that provides a wide range of tools and algorithms for solving optimization problems. Developed by Mirko Maischberger, this framework is built on the principles of modern C programming and offers a flexible and efficient solution for tackling complex optimization challenges. The framework includes a variety of metaheuristic algorithms, including local search and neighbourhood exploration methods. Local search techniques are used to iteratively improve on a given solution by exploring the neighbouring solutions in the search space. This is achieved through the evaluation of a set of moves that can be applied to modify the current solution. By choosing the move that leads to the best improvement in the objective function, the algorithm iterates towards an optimal solution. Neighbourhood exploration methods, on the other hand, involve the exploration of a larger portion of the search space by considering multiple neighbourhoods and potential solutions. These methods aim to balance exploration and exploitation, ensuring that the algorithm can escape local minima and converge towards a global optimum. Overall, COIN-OR METSlib offers a comprehensive set of tools and algorithms that can be customized and adapted to suit a wide range of optimization problems. By leveraging the power of metaheuristics, this framework provides an effective solution for solving complex optimization challenges in various domains. Whether it is local search, neighbourhood exploration, or a combination of both, COIN-OR METSlib is a versatile and efficient framework that can help researchers and practitioners in achieving optimal solutions.