Heuristic value in A* algorithm
By : Meghna Lohani
Date : March 29 2020, 07:55 AM
Any of those help In order to get a heuristic that estimates (lower bounds) the minimum path cost between two nodes there are two possibilities (that I know of): Knowledge about the underlying space the graph is part of

Why greedy algorithm is heuristic, not metaheuristic?
By : user3628641
Date : March 29 2020, 07:55 AM

Heuristic and A* algorithm
By : rathna kumar
Date : March 29 2020, 07:55 AM
it should still fix some issue In this context, a heuristic is a way of providing the algorithm with some form of extra evaluative information, so that the algorithm can find a 'good enough' solution, without exhaustively searching every possible solution. Dijkstra's Algorithm does not use a heuristic. It expands outwards from the start node, and examines every node in the graph in order to find the shortest path. While this is accurate, it can be computationally expensive.

Heuristic For A* Algorithm
By : Łukasz Grzesło
Date : March 29 2020, 07:55 AM
With these it helps A good firstpass search heuristic is to use a greedy algorithm. For example, in a general routeplanning algorithm (find the shortest route between cities) a decent heuristic is to use a greedy algorithm where you always go to the next city that's closest to the destination as the crow flies; this is a lineartime heuristic and never overestimates the solution. In your case, maybe you can use a greedy algorithm in which a garbage truck always goes to the nextclosest garbage node, or the garbage node with the most garbage; I can't get more specific without knowing the details of the four nodes you're using, but you get the idea. Any lineartime algorithm that doesn't overestimate the solution will do, and you can then tweak it in your next pass. (An nlog(n) heuristic is also acceptable in most cases; n^2 is getting awfully expensive.)

How do you unit test an algorithm in C#?
By : Hari Thapa
Date : March 29 2020, 07:55 AM
This might help you Use a table of inputs and known outputs as you described. You need to get the outputs from another implementation of the same algorithm from a source you know is accurate. If you're implementing an algorithm that doesn't have readily available input/output data, then reimplement the algorithm another way, such as in Excel, and generate data you know to be accurate. We do this often with statistical calculations for reports where we can generate data easily in Excel.

