Algorithm introduction:
Dynamic programming is a branch of operations research, which is a mathematical method for solving multi-stage decision-making process optimization problems.
The choice of decision-making at each stage is not determined arbitrarily, it depends on the current state, and affects future development. When the decisions of each stage are determined, a decision sequence is formed, which determines an activity route of the whole process. Such a multi-stage process with a chain structure is called a multi-stage decision-making problem.
Dynamic programming has a wide range of applications in the field of vehicle engineering technology, such as "optimal shift schedule of two-speed transmission", "optimal energy management strategy of hybrid electric vehicle", "optimal path search of grid map", etc.
algorithm thinking
American mathematician Bellrman and others put forward the famous optimization principle in the early 1950s, which transformed the multi-stage decision-making problem into a series of single-stage optimization problems.
For each stage that the best path (best decision-making process) passes through, the path from the beginning of each stage to the end of the whole process must be the best path among all possible paths from the beginning of the stage to the end of the whole process (optimal decision-making ), which is the famous optimization principle proposed by Bellman.
In short, the sub-strategy of an optimal strategy must also be optimal. From this point of view, the algorithm implementation is to find the optimal (shortest) path from the end point until the starting point is found, so that a shortest path can be found.
But there are stages of each decision-making process ahead of time