Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm

摘要

In order to transform three-dimensional space path planning into two-dimensional plane path planning problem and greatly reduce the search time, an intelligent heuristic search algorithm based on artificial intelligence is proposed. The heuristic search algorithm is analyzed and introduced, and A is chosen. A two-dimensional spatial environment model of picking robot path planning is investigated, and a spatial model of picking robot path planning is established by raster method. Then, considering the whole day operation time, the whole day operation time is divided into several periods. With the help of heuristic search algorithm, the most reasonable operation time interval of each period is found, so as to provide reliable reference for the decision-making organization of urban rail transit operation on how to arrange the train rationally. The experimental results show that the improved A <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mo>∗</a:mo> </a:math> algorithm can significantly improve the moving path of the picking robot and make the planned path smoother, which confirms the feasibility and superiority of the improved algorithm. The operation decision of urban rail transit is obtained through experiments. After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635 <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>e</c:mi> </c:math> -001, while the average optimal value is 6.83551939 <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>e</e:mi> </e:math> -001. After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785 <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>e</g:mi> </g:math> -001. The average optimal value is 6.83745935 <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>e</i:mi> </i:math> -001. After 789 iterations, the genetic algorithm obtains the optimal value of 6.83921100 <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:mi>e</k:mi> </k:math> -001, and the average optimal value is 6.84410765 <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:mi>e</m:mi> </m:math> -001. Through the comparative analysis, it can be seen that compared with the other two optimization algorithms, the heuristic search algorithm is significantly better than the other two optimization algorithms, both in terms of the optimal value and the number of optimization iterations. The results show that the heuristic search algorithm is a fast, accurate, and reliable optimization method to solve the problem of accurate scheduling of urban rail transit departure interval. It is proved that the intelligent heuristic search algorithm of artificial intelligence computer can realize the path planning effectively.