15,436 research outputs found
A Potts Neuron Approach to Communication Routing
A feedback neural network approach to communication routing problems is
developed with emphasis on Multiple Shortest Path problems, with several
requests for transmissions between distinct start- and endnodes. The basic
ingredients are a set of Potts neurons for each request, with interactions
designed to minimize path lengths and to prevent overloading of network arcs.
The topological nature of the problem is conveniently handled using a
propagator matrix approach. Although the constraints are global, the
algorithmic steps are based entirely on local information, facilitating
distributed implementations. In the polynomially solvable single-request case
the approach reduces to a fuzzy version of the Bellman-Ford algorithm. The
approach is evaluated for synthetic problems of varying sizes and load levels,
by comparing with exact solutions from a branch-and-bound method. With very few
exceptions, the Potts approach gives legal solutions of very high quality. The
computational demand scales merely as the product of the numbers of requests,
nodes, and arcs.Comment: 10 pages LaTe
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
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