2 results listed
Optimization algorithms yield acceptable results in
the shortest time, even if they cannot always guarantee the best
end result in the given problem. There are classical mathematical
methods and meta-heuristic methods that have become very
popular for solving optimization problems. Meta-heuristic
algorithms can be categorized in many type such as physics based,
social based, biological based, chemistry based, sport based,
swarm based, mathematics based and also hybrid based. In this
study, the Artificial Atom Algorithm (A3) is applied in parallel to
solve the Traveling Salesman Problem (TSP). A3 is chemistrybased
technique that is improved by inspired the compounding
process of atoms and the application of parallel A3 is particularly
easy and promises significant gains in performance especially for
large scale TSP. TSP is one of the route planning problems that
finds the lowest cost path of visiting all the cities on the giving map
and returns to starting point, it was aimed to plan the best route.
The performance of algorithm in terms of the city number, the
route distance and the calculation time of this route will be
examined. An interface will be designed to implement the
application and observe the experimental results.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Ayşe Nur Altintaş Tankül
Burhan Selcuk
In nature, the honeycomb structure is a recurring
phenomenon that is admired for its efficiency, durability, and
optimum utilization of space. These qualities have inspired the
development of man-made honeycomb structures, which are
widely applied in various fields, including engineering,
architecture, and materials science. Among these applications,
the use of honeycomb networks offers significant advantages in
constructing hierarchical structures, such as enhanced
scalability, robustness, and geometric flexibility. In this paper, we
investigate labeling and Hamiltonian path algorithms specifically
designed for Hierarchical Honeycomb Networks (HHMs) by
presenting a novel strategy. The proposed labeling algorithm
systematically generates the coordinates of HHM nodes at
multiple hierarchical levels, utilizing an recursive approach to
ensure consistency and efficiency. Additionally, we investigate a
Hamiltonian feature with the same algorithm designed to define a
path that visits each node exactly once within the HHM
framework. This study demonstrates, through theoretical
analysis and algorithmic implementation, the effectiveness of the
new strategy in optimizing the construction and traversal of
HHM, providing potential insights for applications in network
design, computational geometry, and spatial data organization.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Burhan Selçuk
Ayşe Nur Altintaş Tankül
Saliha Özgüngör
Ali Karcı