Control strategies for parallel mixed integer branch and bound

Mixed integer programs are numerical optimization problems that arise frequently in operations research, particularly in industrial logistics and tactical planning. Their classical solution method is a tree-search branch-and-bound algorithm in which each tree node represents a linear program. This paper describes an implementation of general mixed integer branch-and-bound algorithm that runs on the CM5 family of parallel processors. This code allows varying amounts of centralization, and combines the randomized work-distribution scheme of Karp and Zhang (1993) with a global load-balancing method based on SIMD algorithms. This combination proves effective in an asynchronous MIMD setting.<<ETX>>

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