Bi-objective genetic algorithms for forest management: a comparative study.
Els I. Ducheyne, Robert De Wulf, Bernard De Baets · 2001
Forest management today has become an arduous task. Many stakeholders, including the public, expect the forest to be managed in a sustainable way. This however imposes a considerable burden on the management planning process. As many -- often conflicting -- objectives have to be met, an intuitive approach is no longer sufficient. In this research, the possible use of genetic algorithms to design a forest management plan is investigated. Two genetic algorithms and a random strategy are applied to a real world forest planning problem. Their performance is then compared.