Electromagnetism-like algorithm (EM) is a population-based meta-heuristic which has been proposed to solve continuous problems effectively. In this paper, we present a new meta-heuristic that applies the EM methodology to the single machine scheduling problem. To the best of our knowledge, there are only few researches in solving the combinatorial optimization problem (COP) by EM. This research attempts to employ the random-key concept combining with genetic operators in the hybrid algorithm to obtain the best/optimal schedule for the single machine problems. This new approach attempts to achieve the convergence and diversity effects when it is iteratively applied to solve the problem. This hybrid algorithm is tested on a set of standard test problems available in the literature. The computational results show that this hybrid algorithm performs better than the standard genetic algorithm.
Relation:
Expert Systems with Applications 36(2-1), p.1259-1267
