Random Key Self–Organizing Migrating Algorithm for Permutation Problems

Self–organizing migrating algorithm (SOMA) is a modern stochastic optimization algorithm. It is built upon the principles of evolutionary and swarm computation and has been successfully applied to a variety of theoretical and practical optimization problems. The candidate solutions in SOMA are real– valued and the use of the algorithm for continuous optimization is straightforward. Its application to combinatorial optimization, on the other hand, requires a translation of candidate solutions from continuous search space to discrete problem solution space. In this work, a version of SOMA suitable for permutation problems is proposed and evaluated on two well–known hard permutation problems.