Name
Abstract | ||
|---|---|---|
Investment in landscapes to achieve outcomes that have multiple environmental benefits has become a major priority in many countries. This gives rise to opportunities for mathematical programming methods to provide solutions on where investments could be made on the landscape, to maximise multiple environmental benefits. The problem was formulated as a multi-objective integer programming model, with objective functions representing biodiversity, water run-off and carbon sequestration. We applied a multi-objective Greedy Randomised Adaptive Search Procedure (GRASP) as an evolutionary programming method to find solutions along the Pareto front. This allows the decision maker to explore trade-off's between the objectives. A 142,000ha case study catchment in eastern Australia was used to test the methodology and assess the sensitivity of the different and often competing environmental benefits. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.cor.2006.02.027 | Computers & OR |
Keywords | DocType | Volume |
multi-objective Greedy Randomised Adaptive,Pareto front,carbon sequestration,multi-objective model,case study catchment,Search Procedure,evolutionary programming method,mathematical programming method,multiple environmental benefit,environmental investment decision,multi-objective integer programming model,environmental benefit | Journal | 35 |
Issue | ISSN | Citations |
1 | Computers and Operations Research | 15 |
PageRank | References | Authors |
1.28 | 17 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew J. Higgins | 1 | 129 | 17.59 |
| Stefan Hajkowicz | 2 | 47 | 5.77 |
| Elisabeth Bui | 3 | 28 | 3.52 |