Self-Adjusting of Ternary Search Tries Using Conditional Rotations and Randomized Heuristics

2005 ◽  
Vol 48 (2) ◽  
pp. 200-219 ◽  
Author(s):  
G. H. Badr
Keyword(s):  
Randomized Heuristics

Randomized heuristics for the Max-Cut problem

2002 ◽  
Vol 17 (6) ◽  
pp. 1033-1058 ◽  
Author(s):  
P. Festa ◽  
P.M. Pardalos ◽  
M.G.C. Resende ◽  
C.C. Ribeiro
Keyword(s):  
Randomized Heuristics ◽  
Max Cut Problem

RANDOMIZED HEURISTICS FOR THE MAPPING PROBLEM

1992 ◽  
Vol 04 (04) ◽  
pp. 289-299 ◽  
Author(s):  
S. ARUNKUMAR ◽  
T. CHOCKALINGAM
Keyword(s):  
Mapping Problem ◽  
Randomized Heuristics

scholarly journals Randomized heuristics for the Capacitated Clustering Problem

2017 ◽  
Vol 417 ◽  
pp. 154-168 ◽  
Author(s):  
Anna Martínez-Gavara ◽  
Dario Landa-Silva ◽  
Vicente Campos ◽  
Rafael Martí
Keyword(s):  
Clustering Problem ◽  
Randomized Heuristics

A randomized heuristics for the mapping problem: The genetic approach

1992 ◽  
Vol 18 (10) ◽  
pp. 1157-1165 ◽  
Author(s):  
T Chockalingam ◽  
S Arunkumar
Keyword(s):  
Genetic Approach ◽  
Mapping Problem ◽  
Randomized Heuristics

Performance Analysis of Evolutionary Algorithms for Steiner Tree Problems

2017 ◽  
Vol 25 (4) ◽  
pp. 707-723 ◽  
Author(s):  
Xinsheng Lai ◽  
Yuren Zhou ◽  
Xiaoyun Xia ◽  
Qingfu Zhang
Keyword(s):  
Evolutionary Algorithms ◽  
Steiner Tree ◽  
Minimum Spanning Tree ◽  
Minimum Weight ◽  
Theoretical Work ◽  
Steiner Tree Problem ◽  
Performance Guarantee ◽  
Input Graph ◽  
Randomized Heuristics ◽  
Better Than

The Steiner tree problem (STP) aims to determine some Steiner nodes such that the minimum spanning tree over these Steiner nodes and a given set of special nodes has the minimum weight, which is NP-hard. STP includes several important cases. The Steiner tree problem in graphs (GSTP) is one of them. Many heuristics have been proposed for STP, and some of them have proved to be performance guarantee approximation algorithms for this problem. Since evolutionary algorithms (EAs) are general and popular randomized heuristics, it is significant to investigate the performance of EAs for STP. Several empirical investigations have shown that EAs are efficient for STP. However, up to now, there is no theoretical work on the performance of EAs for STP. In this article, we reveal that the (1+1) EA achieves 3/2-approximation ratio for STP in a special class of quasi-bipartite graphs in expected runtime [Formula: see text], where [Formula: see text], [Formula: see text], and [Formula: see text] are, respectively, the number of Steiner nodes, the number of special nodes, and the largest weight among all edges in the input graph. We also show that the (1+1) EA is better than two other heuristics on two GSTP instances, and the (1+1) EA may be inefficient on a constructed GSTP instance.

Randomized heuristics for the family traveling salesperson problem

2013 ◽  
Vol 21 (1) ◽  
pp. 41-57 ◽  
Author(s):  
L.F. Morán-Mirabal ◽  
J.L. González-Velarde ◽  
M.G.C. Resende
Keyword(s):  
Traveling Salesperson Problem ◽  
The Family ◽  
Randomized Heuristics
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