STUDY PROBLEM 15 (True/False) - If T is the MST of the graph G, for every pair s and t in G, the shortest path from s tot in G is the path from s tot in T. Max-flow algorithm can be used to compute a maximum cardinality matching of a given bipartite graph. Edmond-Karp algorithm is same as Floyd-Fulkerson algorithm except that it just selects the shortest path obtained from BFS (without weights on edges) as the next augmenting path. If a dynamic-programming problem satisfies the optimal-substructure property, then a locally optimal solution is globally optimal. Dynamic programming has the potential to transform exponential-time algorithms to polynomial time. Longest path problem can be solved with dynamic programming with a proper definition of recursive formula. Hill climbing is a local search method in optimization that always provides the optimal solution. If a problem is NP-complete then it is NP-hard. No problem in NP can be solved in polynomial time. If there is a polynomial time algorithm to solve problem A then A is in P. If there is a polynomial time algorithm to solve problem A then A is in NP. Please Help and Answer these 11 true/false questions! I know it's a lot but please answer them all if possible! Thank you!!! STUDY PROBLEM 15 (True/False) - If T is the MST of the graph G, for every pair s and t in G, the shortest path from s tot in G is the path from s tot in T. Max-flow algorithm can be used to compute a maximum cardinality matching of a given bipartite graph. Edmond-Karp algorithm is same as Floyd-Fulkerson algorithm except that it just selects the shortest path obtained from BFS (without weights on edges) as the next augmenting path. If a dynamic-programming problem satisfies the optimal-substructure property, then a locally optimal solution is globally optimal. Dynamic programming has the potential to transform exponential-time algorithms to polynomial time. Longest path problem can be solved with dynamic programming with a proper definition of recursive formula. Hill climbing is a local search method in optimization that always provides the optimal solution. If a problem is NP-complete then it is NP-hard. No problem in NP can be solved in polynomial time. If there is a polynomial time algorithm to solve problem A then A is in P. If there is a polynomial time algorithm to solve problem A then A is in NP. Please Help and Answer these 11 true/false questions! I know it's a lot but please answer them all if possible! Thank you