How does dynamic programming optimize the Matrix Chain Multiplication algorithm?

  • By applying the greedy algorithm.
  • By employing a randomized algorithm.
  • By reusing solutions to overlapping subproblems.
  • By using a divide and conquer approach.
Dynamic programming optimizes the Matrix Chain Multiplication algorithm by reusing solutions to overlapping subproblems. It breaks down the problem into smaller subproblems and solves them only once, storing the solutions in a table to avoid redundant calculations.
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