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Heuristics are proposed relative to optimization algorithms. The optimal algorithm for a problem finds the optimal solution for each instance of the problem.
The heuristic algorithm can be defined like this:
An algorithm based on intuitive or empirical construction, giving a feasible solution for each instance of the combinatorial optimization problem to be solved at an acceptable cost (referring to calculation time and space), the deviation of the feasible solution from the optimal solution is generally not Expected.
At this stage, the heuristic algorithm is mainly based on the pseudo-natural body algorithm, mainly including ant colony algorithm, simulated annealing method, neural network and so on.
In computer science, artificial intelligence, and mathematical optimization, heuristics are a technique for solving problems faster when the classical method is too slow, or for finding an exact solution in a classical method without finding any exact solution. . This is achieved by the optimality, completeness, accuracy or precision of the transaction speed.
In a way, it can be considered a shortcut. A heuristic function, also referred to as inspiration, is a function that replaces the search algorithm based on existing data to decide which branch to follow, in each branch step. For example, it may be close to the exact solution.