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Parallel branch and bound algorithms on hypercube multiprocessors

Branch and Bound (BB) algorithms are a generalization of many search algorithms used in Artificial Intelligence and Operations Research. This paper presents our work on implementing BB algorithms on hypercube multiprocessors. The 0-1 integer linear programming (ILP) problem is taken as an example because it can be implemented to capture the essence of BB search algorithms without too many distracting problem specific details. A BB algorithm for the 0-1 ILP problem is discussed. Two parallel implementations of the algorithm on hypercube multiprocessors are presented. The two implementations demonstrate some of the tradeoffs involved in implementing these algorithms on multiprocessors with no shared memory, such as hypercubes. Experimental results from the NCUBE/six show the performance of the two implementations of the algorithm. Future research work is discussed.