Parallelized solver based on branch and bound method for task scheduling problems in consideration of communication overhead

In order to process the task-graphed parallel solution objects in a shortest time, task scheduling is important. Task scheduling is, however, a strong NP-hard combinatorial optimization problem, and therefore it is difficult to obtain optimal solution in a practical period of time with the task scheduling. For problems additionally extended to take inter-processor communication delay into consideration, it will be more time-consuming to obtain the optimal solution. For these problems, the authors perform parallelized optimal solution search based on branch and bound method. For the sake of effective and high-speed optimal solution search, it is necessary that the lowest limit of the process time from each task for bounding operation to the end of the final task be found out with consideration of the communication time between the tasks. In this study, we developed a method for improving the accuracy of the lower bound and a GUI tool for allowing to manually interfere the search order for the parallel search in order to find out better heuristics useful for the searching.