Previous studies on pipe auto-routing algorithms generally used such algorithms as A∗, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A∗ algorithm in terms of resolution.

以往对管道自动路由算法的研究一般采用A *，Dijkstra，遗传算法，粒子群优化和蚁群优化等算法来满足其自身领域的相关约束，提高输出质量。另一方面，本研究旨在通过将跳转点搜索（JPS）算法应用于管道布线，从而大大提高了寻路速度，该方法所需的搜索成本低于上述算法。但是，现有的JPS仅限于二维空间，只能找到最短的路径。因此，需要对管道布线进行一些改进。管道布线是在三维空间中进行的，管道的路径必须与轴线平行，以最大程度地减少对其他设备的干扰。此外，从经济角度考虑，肘部的数量必须减少到最大，并且路径中的首选空间也必须包括在内。现有的JPS已针对管道布线问题进行了改进，使其可以考虑上述问题。通过与常规A *算法的分辨率比较，验证了该算法的快速寻路速度。