Multiple-Knapsack Optimization in Land Conservation: Results from the first cost-effective conservation program in the US
Messer, Kent D.
Department of Applied Economics and Statistics, University of Delaware, Newark, DE.
The literature on optimizing conservation selection traditionally assumes that the conservation agency makes selections based on a single funding source. However, the reality is that conservation groups often piece together their selections by combining funds from multiple sources. This paper shows that, when conservation programs apply multiple-knapsack optimization (also referred to as simultaneous binary integer programming), substantial increases in social benefits, acreage, and number of parcels preserved can be achieved. In particular, we show that applying a simultaneous optimization model can generate substantially greater benefits than three other approaches: benefit targeting, cost-effectiveness analysis, and sequential optimization. By applying these four methods to data collected from 118 land easement applications in Baltimore County, Maryland, for 2007 through 2009, we show that simultaneous binary integer programming provides greater conservation benefits and preserves more acres of land. This study is the first to use data collected from an ongoing conservation program to quantify the increase in benefits of using a simultaneous optimization approach to achieve truly cost-effective conservation.
Cost effective conservation , Mathematical programming , Land conservation , Multiple knapsack model