MILP for the Multi-objective VM Reassignment Problem
|Title:||MILP for the Multi-objective VM Reassignment Problem||Authors:||Saber, Takfarinas
Murphy, Liam, B.E.
|Permanent link:||http://hdl.handle.net/10197/7205||Date:||11-Nov-2015||Online since:||2015-11-12T13:03:21Z||Abstract:||Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear pro- gramming (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.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Start page:||41||End page:||48||Keywords:||Hybrid- Metaheuristics; Multi-objective optimisation; VM/Machine reassignment; Mixed integer linear programming; Hybrid- metaheuristics||DOI:||10.1109/ICTAI.2015.20||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings of the 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)||Conference Details:||27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Vietri Sul Mare, Italy, 9-11 November, 2015|
|Appears in Collections:||Computer Science Research Collection|
PEL Research Collection
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