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| Content Provider | Springer Nature Link |
|---|---|
| Author | Szkaliczki, Tibor Sobe, Anita Elmenreich, Wilfried |
| Copyright Year | 2015 |
| Abstract | The practical significance of bio-inspired, self-organising methods is rapidly increasing due to their robustness, adaptability and capability of handling complex tasks in a dynamically changing environment. Our aim is to examine an artificial hormone system that was introduced in order to deliver multimedia content in dynamic networks. The artificial hormone algorithm proved to be an efficient approach to solve the problem during the experimental evaluations. In this paper we focus on the theoretical foundation of its goodness. We show that the hormone levels converge to a limit at each node in the typical cases. We form a series of theorems on convergence with different conditions which are built on each other by starting with a specific base case and then we consider more general, practically relevant cases. The theorems are proved by exploiting the analogy between the Markov chains and the artificial hormone system. We examine spatial and temporal monotonicity of the hormone levels as well and give sufficient conditions on monotonic increase. |
| Starting Page | 939 |
| Ending Page | 964 |
| Page Count | 26 |
| File Format | |
| ISSN | 1435246X |
| Journal | Central European Journal of Operations Research |
| Volume Number | 24 |
| Issue Number | 4 |
| e-ISSN | 16139178 |
| Language | English |
| Publisher | Springer Berlin Heidelberg |
| Publisher Date | 2015-07-26 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Self-organizing algorithm Convergence Markov chains Operation Research/Decision Theory |
| Content Type | Text |
| Resource Type | Article |
| Subject | Management Science and Operations Research |
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