Paper Info
Title
A Statistical Comparative Analysis Of Simulated Annealing And Variable Neighborhood Search For The Geographic Clustering Problem
Abstract
This paper describes a factorial statistical study that compares the quality of solutions produced by two heuristics: Simulated Annealing (SA) and Variable Neighborhood Search (VNS). These methods are used to solve the Geographic Clustering Problem (GCP), and the quality of the solutions produced for specific times has been compared. With the goal of comparing the quality of the solutions, where both heuristics participate in an impartial evaluation, time has been the only common element considered for VNS and SA. At this point, two factorial experiments were designed and the corresponding parameters for each heuristic were carefully modeled leaving time as the cost function. In instances of 24 objects, the experiments involved the execution of two sets of tests recording the results of the different response times and the associated values of the objective function for each heuristic and instance conditions. The solution to this problem requires a partitioning process where each group is composed of objects that fulfill better the objective: the minimum accumulated distance from the objects to the centroid of each group. The GCP is a combinatorial NP-hard problem (Bacao, Lobo and Painho, 2004).
Year
Venue
Keywords
2011
COMPUTACION Y SISTEMAS
Algorithms, Design, Experimentation, Geographic Clustering Problem, Heuristics
Field
DocType
Volume
Simulated annealing,Heuristic,Mathematical optimization,Variable neighborhood search,Factorial,Heuristics,Factorial experiment,Cluster analysis,Centroid,Mathematics
Journal
14
Issue
ISSN
Citations 
3
1405-5546
1
PageRank 
References 
Authors
0.63
4
4
Name
Order
Citations
PageRank
Beatriz Bernábe Loranca177.45
José E. Espinosa Rosales210.96
Javier Ramírez Rodríguez341.94
María Auxilio Osorio Lama491.89