A Neighborhood Search Method for Link-Based Tag Clustering

2009 ◽  
pp. 91-103 ◽  
Author(s):  
Jianwei Cui ◽  
Pei Li ◽  
Hongyan Liu ◽  
Jun He ◽  
Xiaoyong Du
Keyword(s):  
Search Method ◽  
Neighborhood Search ◽  
Tag Clustering

Genetic Algorithms, Path Relinking, and the Flowshop Sequencing Problem

1998 ◽  
Vol 6 (1) ◽  
pp. 45-60 ◽  
Author(s):  
Colin R. Reeves ◽  
Takeshi Yamada
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Simulated Annealing Algorithm ◽  
Search Method ◽  
Neighborhood Search ◽  
Search Technique ◽  
Permutation Flowshop ◽  
Sequencing Problem ◽  
Annealing Algorithm ◽  
Tabu Search Method

In a previous paper, a simple genetic algorithm (GA) was developed for finding (approximately) the minimum makespan of the n-job, m-machine permutation flowshop sequencing problem (PFSP). The performance of the algorithm was comparable to that of a naive neighborhood search technique and a proven simulated annealing algorithm. However, recent results have demonstrated the superiority of a tabu search method in solving the PFSP. In this paper, we reconsider the implementation of a GA for this problem and show that by taking into account the features of the landscape generated by the operators used, we are able to improve its performance significantly.

scholarly journals Graphs where Search Methods are Indistinguishable

2021 ◽  
Author(s):  
Matjaž Krnc ◽  
Nevena Pivač
Keyword(s):  
Selection Rule ◽  
Search Method ◽  
Graph Search ◽  
Neighborhood Search ◽  
Graph Searching ◽  
Breadth First Search ◽  
Search Methods ◽  
Depth First Search ◽  
Graph Families ◽  
Vertex Order

Graph searching is one of the simplest and most widely used tools in graph algorithms. Every graph search method is defined using some partic-ular selection rule, and the analysis of the corre-sponding vertex orderings can aid greatly in de-vising algorithms, writing proofs of correctness, or recognition of various graph families. We study graphs where the sets of vertex order-ings produced by two di˙erent search methods coincide. We characterise such graph families for ten pairs from the best-known set of graph searches: Breadth First Search (BFS), Depth First Search (DFS), Lexicographic Breadth First Search (LexBFS) and Lexicographic Depth First Search (LexDFS), and Maximal Neighborhood Search (MNS).

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