Browsing by Author "Tang, Xing"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Comparison of selection methods for easement purchase in Baltimore County(University of Delaware, 2010) Tang, XingUsing data for 118 land parcels that were candidates for easement purchase by various agricultural land conservation programs in Baltimore County from 2007 to 2009, this study compares land selection optimization methods with respect to their efficiency in acquiring conservation benefits and acres within stated budget levels. Specifically, it compares the traditional benefit-targeted method (BT), the cost-effectiveness analysis method (CEA) currently applied by Baltimore County, and two binary integer programming models (BIP-SEQ and BIP-SIM). The BT, CEA, and BIP-SEQ are sequential methods that deal with budgets of multiple programs sequentially. However, since programs differ in how they appraise costs and set criteria for candidate parcels, only BIP-SIM, also known as a multiple-knapsack model in operations research, deals with budgets of multiple programs simultaneously. This study introduces BIP-SIM to the realm of land conservation for the first time to determine whether its ability to work with multiple budgets simultaneously can improve the cost-efficiency of purchasing decisions. The results of this analysis confirm that cost-efficiency increases when moving from BT to CEA, CEA to BIP-SEQ, and BIP-SEQ to BIP-SIM.Item Multiple-Knapsack Optimization in Land Conservation: Results from the first cost-effective conservation program in the US(Department of Applied Economics and Statistics, University of Delaware, Newark, DE., 2014-07) Messer, Kent D.; Kecinski, Maik; Tang, Xing; Hirsch, RobertThe 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.