Algorithm project

●Brute-force

This approach explores all possible combinations of items to find the one that gives the maximum total profit without exceeding the knapsack's capacity. While it guarantees the optimal solution, it becomes impractical for large input sizes due to its exponential time complexity

●Greedy

The greedy algorithm selects items based on the highest profit-to-weight ratio, choosing the most "valuable" items first. It's very fast but does not always guarantee the optimal solution, especially in the 0/1 knapsack version.

●Dynamic programming

This method solves the problem by breaking it into smaller subproblems and storing their results (memoization or tabulation). It is significantly faster than brute force and always finds the optimal solution, making it ideal for moderate-sized problems