The graph-theoretical thickness (shortly thickness)of graph G,
denoted by Φ(G), is the minimum number of planar subgraphs into
which the graph can be decomposed, and a graph that can be
drawn in the plane without any of its edges intersecting is c
alled a
planar graph. determining the thickness of a given graph is known
to be an NP-complete problem.
In this paper we introduce an application heuristic algorithm for
determining the thickness. Our algorithm is based on simulated
annealing optimization scheme which provide the results of the
New-thick (1). We show that the simulated annealing is a efficient
method to obtain good approximation for the thickness when the
number vertices are at most 30 otherwise it is slower.
Finally, we apply this algorithm on the heuristic algorithm Newthick
and we show that the algorithm produces a good
approximation and optimization solution for the thickness, and we
program this algorithm with C++, and running it by laptop has
RAM 2GB and CPU 2.27GHZ.
Operational research science aims to find the optimal solution
to many problems in various life domains. One of the most famous
is the network analysis. Problem. In this paper we introduce an
effective algorithm with linear time O ( n + k ) within it all network
activities are executed within determined period and with a
minimum cost.
The purpose of this article is to shed light on the mechanism
and the procedures of a neuro-fuzzy controller that classifies an
input face into any of the four facial expressions, which are
Happiness, Sadness, Anger and Fear. This program works
a
ccording to the facial characteristic points-FCP which is taken
from one side of the face, and depends, in contrast with some
traditional studies which rely on the whole face, on three
components: Eyebrows, Eyes and Mouth.
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.
