Title :
Genetic Algorithm-based ecosystem for heather management
Author_Institution :
Univ. of Leeds, Leeds
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 grousepsilas needs. We compared this finding with data collected from the field work.
Keywords :
ecology; genetic algorithms; data collection; genetic algorithm-based ecosystem; grouse; heather distributions; heather management; heather moorland ecosystem; spatial relationship; DC generators; Ecosystems; Evolutionary computation; Genetics;
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
DOI :
10.1109/CEC.2008.4631242
