| dc.description.abstract | Owing to the universality of high-tech production technology and high-speed internet infrastructure, remote manufacturing and automatically process scheduling has been much more common these days in modern factory. To reduce both time and financial costs, we must improve the efficiency of algorithm, which can curtail both computing time and obtain majorized and operational path sequence. Hence, developing specialized solution algorithm for restricted condition can’t be more important nowadays.
This research aims to discuss the sequential solution of computer numerical control machine or robotic arm that is subject to designed capacity, which requires suppling materials from one depot through reciprocating motion. Since this kind of problem is similar to the specialized Vehicle Routing Problem (VRP), it is impossible to obtain the best solution in non-deterministic polynomial time. Therefore, we decided to create an algorithm by improving exiting algorithm and combine it with other algorithms for this research. This algorithm should obtain approximate solution in all feasible path sequence and reduce both computational burden and time complexity.
The core concept of this algorithm is based on K-means algorithm and is implemented by C# in this research. The initialized method this algorithm is a customized binary outliers’ method. After that, the algorithm will recursively pick appropriate nodes as clusters and renew the unsatisfied node list till the list is completely traversed. By comparison, this algorithm is confirmed to achieve better performance on path cost than Greedy algorithm, Zipzap sorting method, or typical K-means algorithms when the number of unsorted nodes is above a dozen. Furthermore, the computation time of this algorithm is also far below sorting nodes by complete induction method, which can be deemed as predictable finite time. | en_US |