A note on vector labelling algorithm

1998 ◽  
Vol 43 (5) ◽  
pp. 381-383
Author(s):  
Jianghua Fan ◽  
Zeke Wang
Keyword(s):  
Vector Labelling ◽  
Labelling Algorithm

scholarly journals A HYBRID COLUMN GENERATION ALGORITHM BASED ON METAHEURISTIC OPTIMIZATION

Transport ◽  
2013 ◽  
Vol 31 (4) ◽  
pp. 389-407 ◽  
Author(s):  
Wenbin Hu ◽  
Bo Du ◽  
Ye Wu ◽  
Huangle Liang ◽  
Chao Peng ◽  
...  
Keyword(s):  
Column Generation ◽  
Time Windows ◽  
Path Selection ◽  
Optimization Strategy ◽  
Heuristic Solution ◽  
Generation Algorithm ◽  
Metaheuristic Optimization ◽  
Selection Strategies ◽  
Dual Variables ◽  
Labelling Algorithm

The exact solution and heuristic solution have their own strengths and weaknesses on solving the Vehicle Routing Problems with Time Windows (VRPTW). This paper proposes a hybrid Column Generation Algorithm with Metaheuristic Optimization (CGAMO) to overcome their weaknesses. Firstly, a Modified Labelling Algorithm (MLA) in the sub-problem of path searching is analysed. And a search strategy in CGAMO based on the demand of sub-problem is proposed to improve the searching efficiency. While putting the paths found in the sub-problem into the main problems of CGAMO, the iterations may fall into endless loops. To avoid this problem and keep the main problems in a reasonable size, two conditions on saving the old paths in the main problem are used. These conditions enlarge the number of constraints considered in the iterations to strengthen the limits of dual variables. Through analysing the sub-problem, we can find many useless paths that have no effect on the objective function. Secondly, in order to reduce the number of useless paths and improve the efficiency, this paper proposes a heuristic optimization strategy of CGAMO for dual variables. It is supposed to accelerate the solving speed from the view of on the dual problem. Finally, extensive experiments show that CGAMO achieves a better performance than other state-of-the-art methods on solving VRPTW. The comparative experiments also present the parameters sensitivity analysis, including the different effects of MLA in the different path selection strategies, the characteristics and the applicable scopes of the two pathkeeping conditions in the main problem.

Research on L(2,1)-edge Labelling Algorithm of Graph

2021 ◽  
Author(s):  
Lina Zhu ◽  
Jingwen Li ◽  
Shuai Sun ◽  
Qiaojun Zhang
Keyword(s):  
Labelling Algorithm

Cyclical change and problems of projection

2019 ◽  
pp. 13-32
Author(s):  
Elly van Gelderen
Keyword(s):  
The Other ◽  
The Third ◽  
Cyclical Change ◽  
Diachronic Change ◽  
Feature Sharing ◽  
Linguistic Cycle ◽  
Syntactic Derivation ◽  
Labelling Algorithm

In diachronic change, specifiers are reanalysed as heads and heads as higher heads. When the older specifiers and heads are renewed, a linguistic cycle emerges. Explanations provided for these cycles include structural and featural economy (e.g. van Gelderen 2004; 2011). Chomsky’s (2013, 2015) focus on labelling as unconnected to merge makes it possible to see the cycles in another way, namely as resolutions to labelling problems. The Labelling Algorithm (LA) operates after merge is complete, when a syntactic derivation is transferred to the interfaces. When a head and a phrase merge, the LA determines that the head is the label by Minimal Search. Where two phrases merge, the LA cannot find the head and one of the phrases has to either move or share features with the other. This chapter argues that, in addition to Chomsky’s resolutions to labelling paradoxes, reanalysing a phrase as a head also resolves the paradox. It also shows that the third factor principle minimal search is preferable over feature-sharing. The change from phrase to head is frequent, as eight cross-linguistically attested changes show. In addition, in the renewal stage of a cycle, adjuncts are frequently incorporated as arguments showing a preference of set-merge (feature-sharing) over pair-merge.

scholarly journals A Similarity Normal Clustering Labelling Algorithm for Clustering Network Intrusion Detection

2014 ◽  
Vol 14 (10) ◽  
pp. 969-980
Author(s):  
Zulaiha Ali Othman ◽  
Azuraliza Abu Bakar ◽  
Afaf Muftah Adabashi ◽  
Zurina Muda
Keyword(s):  
Intrusion Detection ◽  
Network Intrusion Detection ◽  
Network Intrusion ◽  
Labelling Algorithm

Labelling Algorithm and Multiple Specifiers.

2017 ◽  
Vol 2017 (94) ◽  
pp. 1-16
Author(s):  
Yong-Ha Kim
Keyword(s):  
Labelling Algorithm
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