DocumentCode
2815855
Title
Approximating a multi-dimensional Pareto front for a land use management problem: A modified MOEA with an epigenetic silencing metaphor
Author
Chikumbo, Oliver ; Goodman, Erik ; Deb, Kalyanmoy
Author_Institution
Scion, Rotorua, New Zealand
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
9
Abstract
Land use management is increasingly becoming complex as the public and governing bodies demand more accountability and transparency in management practices that simultaneously guarantee sustainable production of goods and continued provision of ecosystem services (i.e., public goods with no markets, such as clean air). In this paper we demonstrate a novel form of decision making that will assist in meeting some of these challenges in ensuring sustainability in land use management. We apply a modified Multi-Objective Evolutionary Algorithm (MOEA), influenced by epigenetic silencing, to a farm case study. The result is a set of time-series, farm management strategies and their related spatial arrangements of land uses that satisfy 14 incommensurable and sometimes conflicting objectives, and spatial constraints. The 14 objectives cover economic (i.e. productivity and financials) and environmental issues. Choosing a single strategy from the set for implementation will require social-ethical value judgment determined from preferences and values of multiple decision-makers. This part of the decision making process is beyond the scope of this paper, but will contribute to ongoing research which will make it possible to fully account for the Triple Bottom Line (TBL), characterised by environmental, economic and social elements.
Keywords
Pareto optimisation; decision making; environmental factors; evolutionary computation; farming; land use planning; sustainable development; MOEA; TBL; Triple Bottom Line; decision making; ecosystem services; environmental issues; epigenetic silencing metaphor; farm case study; farm management strategies; land use management problem; multidimensional Pareto front; multiobjective evolutionary algorithm; multiple decision-makers; public goods; social-ethical value judgment; sustainability; sustainable goods production; time-series; Genetics; Lead; USA Councils; Multi-Objective Evolutionary Algorithm (MOEA); Multi-Objective Genetic Algorithm (MOGA); Multi-objective Optimisation Problem (MOP); Pareto front; Reference-point-based Non-dominated Sorting Genetic Algorithm II (R-NSGA-II);
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4673-1510-4
Electronic_ISBN
978-1-4673-1508-1
Type
conf
DOI
10.1109/CEC.2012.6256170
Filename
6256170
Link To Document