Parallel Computations for Solving Multicriteria Mixed-Integer Optimization Problems

The paper discusses a new approach to solving computationally time-consuming multicriteria optimization problems in which some variable parameters can only take on discrete values. Under the proposed approach, the solution of mixed-integer optimization problems is reduced to solving a family of optimization problems where only continuous parameters are used. All problems of the family are solved simultaneously in time-shared mode, where the optimization problem for the next global search iteration is selected adaptively, taking into account the search information obtained in the course of the calculations. The suggested algorithms enable parallel computing on high-performance computing systems. The computational experiments confirm that the proposed approach can significantly reduce the computation volume and time required for solving complex multicriteria mixed-integer optimization problems.

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