MILP for the Multi-objective VM Reassignment Problem
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Title: | MILP for the Multi-objective VM Reassignment Problem | Authors: | Saber, Takfarinas; Ventresque, Anthony; Marques-Silva, Joao; Thorburn, James; 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 | Funding Details: | Lero | 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 | This item is made available under a Creative Commons License: | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ |
Appears in Collections: | Computer Science Research Collection PEL Research Collection |
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