👉 Floyd computing, also known as dynamic programming, is a method for solving complex problems by breaking them down into simpler subproblems and storing the results of these subproblems to avoid redundant computations. Developed by John H. Floyd in 1962, it is particularly useful for optimization problems where the solution can be constructed from optimal solutions of its subproblems. The algorithm iteratively updates a table (often represented as a matrix) where each entry corresponds to the optimal value of a subproblem, using previously computed values. This approach ensures that each subproblem is solved only once, leading to significant efficiency gains over naive recursive methods. Floyd computing is widely applied in fields such as computer science, operations research, and bioinformatics for tasks like sequence alignment, shortest paths, and resource allocation.
