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[Code addition] MULTISTAGE GRAPH
You are given a directed multistage graph with n nodes. The graph is divided into multiple stages, and you need to find the shortest path from the source node (node 0) to the destination node (node n-1) while passing through intermediate stages. Each node belongs to a particular stage, and edges between nodes have associated costs. Use Dynamic Programming to solve this.
About:
One of the most important program in dynamic programming.
The graph is represented as an adjacency matrix, where graph[i][j] denotes the cost of moving from node i to node j:
graph[i][j] = -1 indicates there is no edge from node i to node j.
graph[i][j] ≥ 0 represents the cost of traveling from node i to node j.
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[Code addition]
MULTISTAGE GRAPH You are given a directed multistage graph with n nodes. The graph is divided into multiple stages, and you need to find the shortest path from the source node (node 0) to the destination node (node n-1) while passing through intermediate stages. Each node belongs to a particular stage, and edges between nodes have associated costs. Use Dynamic Programming to solve this.About:
One of the most important program in dynamic programming. The graph is represented as an adjacency matrix, where graph[i][j] denotes the cost of moving from node i to node j: graph[i][j] = -1 indicates there is no edge from node i to node j. graph[i][j] ≥ 0 represents the cost of traveling from node i to node j.
Input:
The adjacency Cost Matrix.
Output:
MInimum cost path and Minimum Cost.
Full Name
SHUVOJIT SAMANTA
Participant Role
GSSOC