A parallel optimal branch-and-bound algorithm for MIN-based multiprocessors

A parallel Optimal Best-First search Branch-and-Bound (B&B) algorithm (obs) is proposed and evaluated for MIN-based multiprocessor systems. The proposed algorithm decomposes a problem into a number of subproblems and each subproblem is processed on a small group of processors. A performance analysis is conducted to estimate the speed-up of the proposed parallel B&B algorithm. It considers both the computation and communication times to evaluate the realistic performance. Simulation data are given, along with analysis results for model validation. It is shown that the proposed algorithm performs better than other reported schemes with its various advantageous features such as: less subproblem evaluations, proper load balancing, and limited scope of remote communication through the network