scholarly journals Shortest path poset of Bruhat intervals

2012 ◽  
Vol 38 (3) ◽  
pp. 585-596 ◽  
Author(s):  
Saúl A. Blanco

2011 ◽  
Vol DMTCS Proceedings vol. AO,... (Proceedings) ◽  
Author(s):  
Saúl A. Blanco

International audience Let $[u,v]$ be a Bruhat interval and $B(u,v)$ be its corresponding Bruhat graph. The combinatorial and topological structure of the longest $u-v$ paths of $B(u,v)$ has been extensively studied and is well-known. Nevertheless, not much is known of the remaining paths. Here we describe combinatorial properties of the shortest $u-v$ paths of $B(u,v)$. We also derive the non-negativity of some coefficients of the complete mcd-index of $[u,v]$. Soit $[u,v]$ un intervalle de Bruhat et $B(u,v)$ le graphe de Bruhat associé. La structure combinatoire et topologique des plus longs chemins de $u$ à $v$ dans $B(u,v)$ est bien comprise, mais on sait peu de chose des autres chemins. Nous décrivons ici les propriétés combinatoires des plus courts de chemins de $u$ à $v$. Nous prouvons aussi que certains coefficients du mcd-indice complet de $[u,v]$ sont positifs.



Author(s):  
Achmad Fanany Onnilita Gaffar ◽  
Agusma Wajiansyah ◽  
Supriadi Supriadi

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.





2020 ◽  
Vol 9 (10) ◽  
pp. 7803-7809 ◽  
Author(s):  
J. P. Praveena ◽  
N. S. Stalin ◽  
A. Rajkumar


2007 ◽  
Author(s):  
W. M. Carlyle ◽  
Johannes O. Royset ◽  
R. K. Wood


Author(s):  
Parimala Mani ◽  
Biju Vasudevan ◽  
Murali Sivaraman


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