Variable Neighborhood Search for Google Machine Reassignment problem

We present a hybrid method to efficiently solve Google Machine Reassignment problem (MRP), the problem proposed at ROADEF/EURO Challenge 2012 competition. We study, implement, combine and empirically examine different local search neighborhoods to solve the set of available instances. Intensification and diversification of search is achieved through the suitable change of the objective function and sorting the processes. We present results obtained with the solver that respect the given computational time of 5 minutes. Some of the obtained results are proven to be optimal or near optimal. With the presented method we were ranked first at ROADEF/EURO Challenge 2012 competition.