The all-nodes shortest paths problem is undoubtedly one of
the most basic problems in algorithmic graph theory. In this paper,
we introduce simple and efficient algorithm for all nodes shortest
paths problem for directed (undirected) graphs. In th
is problem, we
find the shortest path from a given source node to all other nodes in
the graph, in which the shortest path is a path with minimum cost,
i.e., sum of the edge weights.
We proved that the complexity of the proposed algorithm in
this paper depends only on the edges graph, and we show that the
time of implementation of this algorithm is linear time O(m) and
This is considered the best times of the algorithms at all. And
a Comparison between complexity of proposed algorithm and the
famous shortest path algorithms have been made, and the obtained
results have shown that the complexity of the proposed algorithm
is best.
In this paper, we introduce an Effective algorithm to find the
shortest path in Multiple – Source Graph, by choosing the path
between the source and the distance that gives at least the length of
the path down to the sink. This algorithm is based
on the principle
of iteration to access the optimal solution of the shortest-path
problem, Where the algorithm steps are repeated for all the darts in
the Graph. We proved that the time of implementation of the
proposed algorithm in this paper is linear time O(n+L) and This is
considered the best times of the algorithms at all.
The shortest path problem can be categorized in to two
different problems; single source shortest path problem (SSSP) and
all pair shortest algorithm (APSP). In this paper, analysis and
comparison between complexity of the famous shortest path
al
gorithms have been made, and the obtained results have shown
that researchers have got remarkable success in designing better
algorithms in the terms of time complexity to solve shortest path
algorithms.
In this research we are studying the possibility of contributing in
solving the problem of the Traveling Salesman Problem, which is
a problem of the type NP-hard . And there is still no algorithm
provides us with the Optimal solution to this problem . All the
algorithms used to give solutions which are close to the optimal
one .
This research tries to address the problem of Ibn Wahab Al-Kateb Types of Rhetorics
according to Al-Jahiz and Ibn Wahab Al-Kateb
accusing Abi Othman Al-Jahiz of not giving rhetorics what it is worth, and of not
studying it thoroughfully. Ibn Wahab
claimed completing what is missed through his
detailed study of the types of rhetorics, which are, to a large extent, similar to the types of
rhetorics according to Abi Othman.The later referred to the importance of the relation
between pronunciation, meaning and the necessity of the accordance between the two. In
addition, meaning is prior to pronunciation because it depends upon thought and
contemplation. He describes the types of rhetorics in a pyramidal sequential through levels
that stem-- and result-- from each other.
Similarly, Ibn wahab considers that the types of rhetorics result from each other.
These types, according to critics, are a process of a birth of these forms.
Despite the big similarity of the types of rhetorics according to both Ibn Wahab Al-
Kateb and Abi Othman Al-Jahiz, the first was not only a transcriber, but also he added and
clarified in certain areas. He exclusively talked about writers and classified them in one of
five: transcript writer, pronunciation writer, contract writer, judgment writer and
management writer. He also mentioned the most important features that a transcript writer
must have and divided writers into three levels. He extended in talking about the types of
handwriting and the forms of pens. These issues were dropped by Al-Jahiz when talking
about the types of rhetorics.
As it’s known, The Graph k-Colorability Problem (GCP) is a wellknown
NP-Hard Problem. This problem consists in finding the k
minimum number of colors to paint the vertices of a graph in such a way
that any two adjoined vertices, which are connecte
d by an edge, have
always different colors. In another words how can we color the edges of a
graph in such a way that any two edges joined by a vertex have always
different colors? In this paper we introduce a new effective algorithm for
coloring the edges of the graph. Our proposed algorithm enables us to
achieve a Continuously Edge Coloring (CEC) for a set of known graphs.
