Branch and Bound
Branch and bound is a systematic method used to solve optimization problems, such as finding the best solution from a set of possible choices. It works by dividing the problem into smaller parts (branching), evaluating their potential solutions, and eliminating those that don't meet certain criteria (bounding). This process continues until the best solution is found or all possibilities are explored. It’s like exploring a large maze: you check branches of the maze, discard paths that lead nowhere, and keep track of the best route until you find your way out efficiently.
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Branch-and-Bound is a problem-solving algorithm used in optimization, particularly for finding the best solution among many possible options. It works by dividing the problem into smaller, manageable parts (branching) and evaluating them to determine their potential (bounding). If a part cannot yield a better solution than one already found, it's disregarded. This process continues until all possibilities are explored or eliminated, enabling efficient discovery of the optimal solution. It's commonly applied in areas like scheduling, routing, and resource allocation, effectively balancing comprehensive search with practical limits on time and resources.