Constraint-based large neighborhood search for machine reassignment

This paper addresses a process-to-machine reassignment problem arising in cloud computing environments. The problem formulation has been posed as the ROADEF/EURO challenge 2012. Our presented approach is basically a large neighborhood search that iteratively improves a given solution. In each iteration only a subset of processes is considered for reassignment and the new assignments are evaluated by a constraint program. In this paper we present our general solution approach. Furthermore, we evaluate different process selection strategies and other optimization means to improve the performance on larger instances. In addition, we present a simple way to compute tight lower bounds of the necessary costs.