Parallel Global Optimization for Non-convex Mixed-Integer Problems

Abstract

The paper considers the mixed-integer global optimization problems. A novel parallel algorithm for solving the problems of this class based on the index algorithm for solving the continuous global optimization problems has been proposed. The comparison of this algorithm with known analogs demonstrates the efficiency of the developed approach. The proposed algorithm allows an efficient parallelization including the employment of the graphics accelerators. The results of performed numerical experiments (solving a series of 100 multiextremal mixed-integer problems) confirm a good speedup of the algorithm with the use of GPU.