Solving Scheduling Problems with Randomized and Parallelized Brute-Force Approach

Abstract

Most of the scheduling problems are NP-hard problems. Thus, they do not have polynomial-time solutions. The literature review provides hundreds of methods and approaches to find polynomial-time near-optimal solutions. Most of these approaches are based on genetic algorithms. Genetic algorithms have the power of scanning most of the solution space, and they are not vulnerable to hill-climbing phenomena. However, as this paper shows, genetic algorithms cannot be used if the rate of production of healthy offspring is very low. Hence, this paper proposes a novel approach that is based on randomized brute-force and inspired by genetic algorithms. Also, the proposed approach uses parallel processing.