scholarly journals A Comprehensive Comparison of Label Setting Algorithm and Dynamic Programming Algorithm in Solving Shortest Path Problems

2021 ◽  
Vol 13 (5) ◽  
pp. 14
Author(s):  
Douglas Yenwon Kparib ◽  
John Awuah Addor ◽  
Anthony Joe Turkson
Keyword(s):  
Dynamic Programming ◽  
Shortest Path ◽  
Shortest Paths ◽  
Dynamic Programming Algorithm ◽  
Minimum Cost ◽  
Programming Algorithm ◽  
Shortest Path Problems ◽  
Comprehensive Comparison ◽  
Paper Label ◽  
Label Setting Algorithm

In this paper, Label Setting Algorithm and Dynamic Programming Algorithm had been critically examined in determining the shortest path from one source to a destination. Shortest path problems are for finding a path with minimum cost from one or more origin (s) to one or more destination(s) through a connected network. A network of ten (10) cities (nodes) was employed as a numerical example to compare the performance of the two algorithms. Both algorithms arrived at the optimal distance of 11 km, which corresponds to the paths 1→4→5→8→10 ,1→3→5→8→10 , 1→2→6→9→10  and  1→4→6→9→10 . Thus, the problem has multiple shortest paths. The computational results evince the outperformance of Dynamic Programming Algorithm, in terms of time efficiency, over the Label Setting Algorithm. Therefore, to save time, it is recommended to apply Dynamic Programming Algorithm to shortest paths and other applicable problems over the Label-Setting Algorithm.

scholarly journals Penerapan Algoritma Dynamic Programing pada Pergerakan Lawan dalam Permainan Police and Thief

2019 ◽  
Vol 2 (2) ◽  
pp. 114
Author(s):  
Insidini Fawwaz ◽  
Agus Winarta
Keyword(s):  
Artificial Intelligence ◽  
Dynamic Programming ◽  
Search Algorithm ◽  
Dynamic Programming Algorithm ◽  
Minimum Cost ◽  
Programming Algorithm ◽  
Shortest Route ◽  
Basic Meaning ◽  
Dynamic Programing ◽  
Approximate Distance

<p class="8AbstrakBahasaIndonesia"><em>Games have the basic meaning of games, games in this case refer to the notion of intellectual agility. In its application, a Game certainly requires an AI (Artificial Intelligence), and the AI used in the construction of this police and thief game is the dynamic programming algorithm. This algorithm is a search algorithm to find the shortest route with the minimum cost, algorithm dynamic programming searches for the shortest route by adding the actual distance to the approximate distance so that it makes it optimum and complete. Police and thief is a game about a character who will try to run from </em><em>police.</em><em> The genre of this game is arcade, built with microsoft visual studio 2008, the AI used is the </em><em>Dynamic Programming</em> <em>algorithm which is used to search the path to attack players. The results of this test are police in this game managed to find the closest path determined by the </em><em>Dynamic Programming</em> <em>algorithm to attack players</em></p>

RANKING VALID TOPOLOGIES OF THE SECONDARY STRUCTURE ELEMENTS USING A CONSTRAINT GRAPH

2011 ◽  
Vol 09 (03) ◽  
pp. 415-430 ◽  
Author(s):  
KAMAL AL NASR ◽  
DESH RANJAN ◽  
MOHAMMAD ZUBAIR ◽  
JING HE
Keyword(s):  
Dynamic Programming ◽  
Secondary Structure ◽  
Protein Complexes ◽  
Dynamic Programming Algorithm ◽  
Weighted Graph ◽  
Minimum Cost ◽  
Programming Algorithm ◽  
Programming Approach ◽  
Constraint Graph ◽  
Density Maps

Electron cryo-microscopy is a fast advancing biophysical technique to derive three-dimensional structures of large protein complexes. Using this technique, many density maps have been generated at intermediate resolution such as 6–10 Å resolution. Although it is challenging to derive the backbone of the protein directly from such density maps, secondary structure elements such as helices and β-sheets can be computationally detected. Our work in this paper provides an approach to enumerate the top-ranked possible topologies instead of enumerating the entire population of the topologies. This approach is particularly practical for large proteins. We developed a directed weighted graph, the topology graph, to represent the secondary structure assignment problem. We prove that the problem of finding the valid topology with the minimum cost is NP hard. We developed an O(N2 2N) dynamic programming algorithm to identify the topology with the minimum cost. The test of 15 proteins suggests that our dynamic programming approach is feasible to work with proteins of much larger size than we could before. The largest protein in the test contains 18 helical sticks detected from the density map out of 33 helices in the protein.

scholarly journals A dynamic programming algorithm for solving the k-Color Shortest Path Problem

2020 ◽  
Author(s):  
Daniele Ferone ◽  
Paola Festa ◽  
Serena Fugaro ◽  
Tommaso Pastore
Keyword(s):  
Mathematical Model ◽  
Dynamic Programming ◽  
Branch And Bound ◽  
Shortest Path ◽  
Dynamic Programming Algorithm ◽  
Shortest Path Problem ◽  
Programming Algorithm ◽  
Colored Graph ◽  
Transmission Networks ◽  
The Mathematical Model

Abstract Several variants of the classical Constrained Shortest Path Problem have been presented in the literature so far. One of the most recent is the k-Color Shortest Path Problem ($$k$$ k -CSPP), that arises in the field of transmission networks design. The problem is formulated on a weighted edge-colored graph and the use of the colors as edge labels allows to take into account the matter of path reliability while optimizing its cost. In this work, we propose a dynamic programming algorithm and compare its performances with two solution approaches: a Branch and Bound technique proposed by the authors in their previous paper and the solution of the mathematical model obtained with CPLEX solver. The results gathered in the numerical validation evidenced how the dynamic programming algorithm vastly outperformed previous approaches.

scholarly journals Prograph Based Analysis of Single Source Shortest Path Problem with Few Distinct Positive Lengths

2011 ◽  
Vol 1 (4) ◽  
pp. 90-97
Author(s):  
B. Bhowmik ◽  
S. Nag Chowdhury
Keyword(s):  
Shortest Path ◽  
Directed Graphs ◽  
Algorithm Design ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Single Source ◽  
Comparison Study ◽  
Design Technique ◽  
Shortest Path Problems ◽  
Finite Directed Graphs

In this paper we propose an experimental study model S3P2 of a fast fully dynamic programming algorithm design technique in finite directed graphs with few distinct nonnegative real edge weights. The Bellman-Ford’s approach for shortest path problems has come out in various implementations. In this paper the approach once again is re-investigated with adjacency matrix selection in associate least running time. The model tests proposed algorithm against arbitrarily but positive valued weighted digraphs introducing notion of  Prograph that speeds up finding the shortest path over previous implementations. Our experiments have established abstract results with the intention that the proposed algorithm can consistently dominate other existing algorithms for Single Source Shortest Path Problems. A comparison study is also shown among Dijkstra’s algorithm, Bellman-Ford algorithm, and our algorithm.

scholarly journals DMGA: A Distributed Shortest Path Algorithm for Multistage Graph

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Huanqing Cui ◽  
Ruixue Liu ◽  
Shaohua Xu ◽  
Chuanai Zhou
Keyword(s):  
Shortest Path ◽  
Large Scale ◽  
Structural Characteristics ◽  
Shortest Paths ◽  
Dynamic Programming Algorithm ◽  
Special Kind ◽  
Graph Algorithm ◽  
Shortest Path Problem ◽  
Programming Algorithm ◽  
Classical Dynamic

The multistage graph problem is a special kind of single-source single-sink shortest path problem. It is difficult even impossible to solve the large-scale multistage graphs using a single machine with sequential algorithms. There are many distributed graph computing systems that can solve this problem, but they are often designed for general large-scale graphs, which do not consider the special characteristics of multistage graphs. This paper proposes DMGA (Distributed Multistage Graph Algorithm) to solve the shortest path problem according to the structural characteristics of multistage graphs. The algorithm first allocates the graph to a set of computing nodes to store the vertices of the same stage to the same computing node. Next, DMGA calculates the shortest paths between any pair of starting and ending vertices within a partition by the classical dynamic programming algorithm. Finally, the global shortest path is calculated by subresults exchanging between computing nodes in an iterative method. Our experiments show that the proposed algorithm can effectively reduce the time to solve the shortest path of multistage graphs.

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