Paper Info
Title
Solving the facility location and design (1∣1)-centroid problem via parallel algorithms.
Abstract
Abstract Several parallel strategies for solving a centroid problem are presented. In the competitive location problem considered in this paper, the aim is to maximize the profit obtained by a chain (the leader) knowing that a competitor (the follower) will react by locating another single facility after the leader locates its own facility. A global optimization memetic algorithm called UEGO_cent.SASS was proposed to cope with this hard-to-solve optimization problem. Now, five parallel implementations of the optimization algorithm have been developed. The use of several processors, and hence more computational resources, allows us to solve bigger problems and to implement new methods which increase the robustness of the algorithm at finding the global optimum. A computational study comparing the new parallel methods in terms of efficiency and effectiveness has been carried out.
Year
DOI
Venue
2011
10.1007/s11227-011-0605-5
The Journal of Supercomputing
Keywords
Field
DocType
Parallelism,Master-slave,Coarse-grain,Evolutionary algorithm,Nonlinear bilevel programming problem,Centroid (or Stackelberg) problem
Memetic algorithm,Mathematical optimization,Evolutionary algorithm,Global optimization,Computer science,Parallel algorithm,Robustness (computer science),Facility location problem,1-center problem,Optimization problem,Distributed computing
Journal
Volume
Issue
ISSN
58
3
1573-0484
Citations 
PageRank 
References 
3
0.45
4
Authors
4
Name
Order
Citations
PageRank
Juana López Redondo1394.98
José-jesús Fernández24610.63
Inmaculada García3528.82
P.M. Ortigosa49816.37