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The multi-objective integer programming problems in large scale are considered time consuming. In the past, mathematical structures were used that can get benefits of high processing powers and parallel processing. The Branch and Bound (B&B) algorithm is one of the most used methods to solve combinatorial optimization problems. A general approach to generate all non-dominated solutions of the multi-objective integer programming (MOIP) Problem is developed. In this paper, a supervisor-master-sub-master-worker algorithm to solve large scale integer multi-objective problems that can get the benefits of mathematical structures and high processing powers has been proposed. This approach addresses several issues related to the characteristics of the algorithm itself and the properties of parallel computing systems. From the solved benchmark example this algorithm proved to provide a considerable high performance. Results show that a consistently better efficiency can be achieved in solving integer equations, providing reduction of time.