Please use this identifier to cite or link to this item:
|Title:||Combining biased random sampling with metaheuristics for the facility location problem in distributed computer systems|
|Author:||Cabrera Añon, Guillem |
González Martín, Sergio
Juan Pérez, Ángel Alejandro
Grasman, Scott Erwin
Marquès Puig, Joan Manuel
|Publisher:||Winter Simulation Conference (WSC). Proceedings|
|Citation:||Cabrera, G., Gonzalez-Martin, S., Juan, A.A., Marquès, J.M. & Grasman, S.E. (2014). Combining biased random sampling with metaheuristics for the facility location problem in distributed computer systems. Winter Simulation Conference (WSC). Proceedings, 2014(), 3000-3011. doi: 10.1109/WSC.2014.7020139|
|Series/Report no.:||Winter Simulation Conference, Savannah, EUA, 7-10, desembre de 2014|
|Abstract:||This paper introduces a probabilistic algorithm for solving the well-known Facility Location Problem (FLP), an optimization problem frequently encountered in practical applications in fields such as Logistics or Telecommunications. Our algorithm is based on the combination of biased random sampling -using a skewed probability distribution- with a metaheuristic framework. The use of random variates from a skewed distribution allows to guide the local search process inside the metaheuristic framework which, being a stochastic procedure, is likely to produce slightly different results each time it is run. Our approach is validated against some classical benchmarks from the FLP literature and it is also used to analyze the deployment of service replicas in a realistic Internet-distributed system.|
|Appears in Collections:||Articles|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.