Paper Info
Title
Experimental Comparison of Greedy Randomized Adaptive Search Procedures for the Maximum Diversity Problem
Abstract
The maximum diversity problem (MDP) consists of identifying optimally diverse subsets of elements from some larger collection. The selection of elements is based on the diversity of their characteristics, calculated by a function applied on their attributes. This problem belongs to the class of NP-hard problems. This paper presents new GRASP heuristics for this problem, using different construction and local search procedures. Computational experiments and performance comparisons between GRASP heuristics from literature and the proposed heuristics are provided and the results are analyzed. The tests show that the new GRASP heuristics are quite robust and find good solutions to this problem.
Year
DOI
Venue
2004
10.1007/978-3-540-24838-5_37
Lecture Notes in Computer Science
Keywords
Field
DocType
computer experiment,greedy randomized adaptive search procedure,local search,np hard problem
Mathematical optimization,GRASP,Variable neighborhood search,Adaptive method,Computer science,Characteristic function (probability theory),Heuristics,Local search (optimization)
Conference
Volume
ISSN
Citations 
3059
0302-9743
31
PageRank 
References 
Authors
2.46
5
3
Name
Order
Citations
PageRank
Geiza C. Silva1523.44
Luiz S. Ochi216012.54
Simone L. Martins325320.94