MILP for the Multi-objective VM Reassignment Problem

Takfarinas Saber, Anthony Ventresque, Joao Marques-Silva, James Thorburn, Liam Murphy
2015 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)  
Machine Reassignment is a challenging problem for constraint programming (CP) and mixed-integer linear programming (MILP) approaches, especially given the size of data centres. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP or MILP to obtain good results in this context. As a result, the first approaches to address this problem have been based on other optimisation methods, including metaheuristics. In this paper we study
more » ... er which conditions a mixed-integer optimisation solver, such as IBM ILOG CPLEX, can be used for the Multi-objective Machine Reassignment Problem. We show that it is useful only for small or medium-scale data centres and with some relaxations, such as an optimality tolerance gap and a limited number of directions explored in the search space. Building on this study, we also investigate a hybrid approach, feeding a metaheuristic with the results of CPLEX, and we show that the gains are important in terms of quality of the set of Pareto solutions (+126.9% against the metaheuristic alone and +17.8% against CPLEX alone) and number of solutions (8.9 times more than CPLEX), while the processing time increases only by 6% in comparison to CPLEX for execution times larger than 100 seconds.
doi:10.1109/ictai.2015.20 dblp:conf/ictai/SaberVMTM15 fatcat:nhnk5dk7mrfn3nvnhdvb7qwxhu