In this paper, we are concerned with the K-shortest loopless path problem. The MPS algorithm, recently proposed by Martins et al., finds paths efficiently because it solves the shortest path problem only one time unlike other algorithms. But its computational complexity has not been known yet. We propose a few techniques by which the MPS algorithm can be implemented efficiently. First, we use min-heap data structure for the storage of candidate paths in order to reduce searching time for finding minimum distance path. Second, we prevent the eliminated paths from reentering in the list of candidate paths by lower bounding technique. Finally, we choose the source mode as a deviation node, by which selection time for the deviation node is reduced and the performance is improved in spite of the increase of the total number of candidate paths.