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MILP for the Multi-objective VM Reassignment Problem
Date Issued
2015-11-11
Date Available
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.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Lero
Type of Material
Conference Publication
Publisher
IEEE
Start Page
41
End Page
48
Language
English
Status of Item
Peer reviewed
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
This item is made available under a Creative Commons License
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