AUGMENTED LAGRANGEAN RELAXATIONS IN GENERAL MIXED INTEGER PROGRAMMING

Abstract A new relaxation is presented for the general mixed integer programing problem. It is proved that this relaxation is always at least as good, end in one demonstrated case better, than some other known relaxations. Various aspects of the implementation of the relaxation in a branch-and-bound algorithm are discussed. Numerical examples are given to demonstrate the feasibility of the approach.

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