Details
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3734-3739 |
| Number of pages | 6 |
| ISBN (electronic) | 9781509006229, 9781509006236 |
| ISBN (print) | 9781509006243 |
| Publication status | Published - 2016 |
| Event | 2016 IEEE Congress on Evolutionary Computation - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 |
Abstract
Swarm algorithms are often used for the generation of graphs. The generated graphs are mostly planar, inexpensive and fault-tolerant. In this work we evaluate the graphs produced by a swarm algorithm with respect to the properties and the quality of the found graphs and to the runtime requirements. The algorithm under consideration is essentially a simulation of the foraging of the slime mold Physarum polycephalum. Especially emphasized are the properties of the algorithm, since its deployment in many other works is limited to the existence of a graph solution, not reporting however the quality of the graph and runtime requirements of the algorithm. We compare the quality of the resulting graphs and the runtime of the algorithm to classical algorithms from graph theory. Our results show that the slime mold algorithm has some interesting features, however it is not the best means to construct graphs of large sets of nodes in terms of efficiency of the algorithm or quality of the outcome.
ASJC Scopus subject areas
- Computer Science(all)
- Artificial Intelligence
- Mathematics(all)
- Modelling and Simulation
- Computer Science(all)
- Computer Science Applications
- Mathematics(all)
- Control and Optimization
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2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 3734-3739 7744262.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - On the quality of graphs generated by swarm algorithms
AU - Becker, Matthias
PY - 2016
Y1 - 2016
N2 - Swarm algorithms are often used for the generation of graphs. The generated graphs are mostly planar, inexpensive and fault-tolerant. In this work we evaluate the graphs produced by a swarm algorithm with respect to the properties and the quality of the found graphs and to the runtime requirements. The algorithm under consideration is essentially a simulation of the foraging of the slime mold Physarum polycephalum. Especially emphasized are the properties of the algorithm, since its deployment in many other works is limited to the existence of a graph solution, not reporting however the quality of the graph and runtime requirements of the algorithm. We compare the quality of the resulting graphs and the runtime of the algorithm to classical algorithms from graph theory. Our results show that the slime mold algorithm has some interesting features, however it is not the best means to construct graphs of large sets of nodes in terms of efficiency of the algorithm or quality of the outcome.
AB - Swarm algorithms are often used for the generation of graphs. The generated graphs are mostly planar, inexpensive and fault-tolerant. In this work we evaluate the graphs produced by a swarm algorithm with respect to the properties and the quality of the found graphs and to the runtime requirements. The algorithm under consideration is essentially a simulation of the foraging of the slime mold Physarum polycephalum. Especially emphasized are the properties of the algorithm, since its deployment in many other works is limited to the existence of a graph solution, not reporting however the quality of the graph and runtime requirements of the algorithm. We compare the quality of the resulting graphs and the runtime of the algorithm to classical algorithms from graph theory. Our results show that the slime mold algorithm has some interesting features, however it is not the best means to construct graphs of large sets of nodes in terms of efficiency of the algorithm or quality of the outcome.
UR - http://www.scopus.com/inward/record.url?scp=85008259027&partnerID=8YFLogxK
U2 - 10.1109/CEC.2016.7744262
DO - 10.1109/CEC.2016.7744262
M3 - Conference contribution
AN - SCOPUS:85008259027
SN - 9781509006243
SP - 3734
EP - 3739
BT - 2016 IEEE Congress on Evolutionary Computation, CEC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Congress on Evolutionary Computation
Y2 - 24 July 2016 through 29 July 2016
ER -