Parallel Branch and Bound Algorithms for Integer and Mixed Integer Linear Programming Problems under PVM

In this paper we consider efficient parallel Branch and Bound (B&B) algorithms for Integer Linear Programming (ILP) and Mixed ILP (MILP) Problems in a MIMD distributed memory environment. The algorithms are scalable and run on a cluster of workstations under PVM. To achieve efficient parallel implementation and to speedup the computations in our approach, firstly, we apply various preprocessing techniques in order to reduce the problem size prior to optimization, and secondly, we apply B&B algorithms with dynamic distribution of tasks among the processors.

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