A Survey and a Classification of Recent Approaches to Solve the Google Machine Reassignment Problem

Optimizing the usage of resources is an important topic in the development of technologies and computational services. The Google Machine Reassignment Problem is an NP-hard problem that is related to this crucial situation, based on the assignation of a set of processes into a set of machines trying to reduce several costs. This problem was proposed for the 2012 ROADEF/EURO challenge and since its introduction, many approaches have been proposed in order to reach better quality solutions or improve the execution time of the existing techniques. In this work, we review a significant number of recently proposed approaches. Due to the number of published papers, it is difficult to ascertain the level of current research in this area. In order to provide a useful guide to new interested researchers, we include up-to-date best-known results for benchmark instances, an analysis of the design of each technique and details of the experimental setup. We also present a classification and a taxonomy of the reviewed approaches based on the design of these techniques, considering their main components and the structure of the search strategies.