Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies

Embedded systems have become an essential part of our lives, thanks to their evolution in the recent years, but the main drawback is their power consumption. This paper is focused on improving the memory allocation of embedded systems to reduce their power consumption. We propose a parallel variable neighborhood search algorithm for the dynamic memory allocation problem, and compare it with the state of the art. Computational results and statistical tests applied show that the proposed algorithm produces significantly better outcomes than the previous algorithm in shorter computing time.