Abstract
This paper applies Genetic Algorithms (GA) to simulate a heather moorland ecosystem. We investigate, in this ecosystem how to manage heather for the benefits of survival and reproduction of grouse. A GA candidate solution is a grid, representing spatial relationship of three types of heather. From solutions provided by GA, we have found that the diversity of neighborhood and its distribution are essential. The evenly diversified heather distributions emerge as the best fit solutions for grouse's needs. We compared this finding with data collected from the field work.
| Original language | English |
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| Title of host publication | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 |
| Pages | 3282-3288 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China Duration: 1 Jun 2008 → 6 Jun 2008 |
Publication series
| Name | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 |
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Conference
| Conference | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 |
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| Country/Territory | China |
| City | Hong Kong |
| Period | 1/06/08 → 6/06/08 |
Cite this
Jin, N. (2008). Genetic Algorithm-based ecosystem for heather management. In 2008 IEEE Congress on Evolutionary Computation, CEC 2008 (pp. 3282-3288). Article 4631242 (2008 IEEE Congress on Evolutionary Computation, CEC 2008). https://doi.org/10.1109/CEC.2008.4631242