Paper Info
Title
MILP for the Multi-objective VM Reassignment Problem
Abstract
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 under 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.
Year
DOI
Venue
2015
10.1109/ICTAI.2015.20
IEEE International Conference on Tools with Artificial Intelligence
Keywords
Field
DocType
Multi-objective Optimisation, VM/Machine Reassignment, Mixed Integer Linear Programming, Hybrid-Metaheuristics
Integer,Mathematical optimization,Computer science,Constraint programming,Server,Integer programming,Solver,Transient analysis,Pareto principle,Metaheuristic
Conference
ISSN
Citations 
PageRank 
1082-3409
1
0.35
References 
Authors
12
5
Name
Order
Citations
PageRank
Takfarinas Saber1254.90
Anthony Ventresque210817.08
Joao Marques-Silva31947124.04
James Thorburn4264.11
Liam Murphy581174.94