Geology topics

Bradley J. Udell

Publications and source records attributed to Bradley J. Udell.

2 recordsLinked to original sources

USGS2021

SiteOpt: An open-source R-package for site selection and portfolio optimization

Conservation planning involves identifying and selecting actions to best achieve objectives for managing natural, social and cultural resources. Conservation problems are often high dimensional when specified as combinatorial or portfolio problems and when multiple competing objectives are considered at varying spatial and temporal scales. Although analytical techniques such as modern portfolio theory (MPT) have been developed to address these complex problems, open source computational platforms for executing these approaches are not readily available. We present a user-friendly R-package called SiteOpt for optimization of binary decisions while explicitly considering environmental or economic uncertainty and the risk tolerance of decision makers. We illustrate the package with spatially-explicit site selection problems (i.e. spatial conservation planning), including an option for divestment (i.e. selling assets), when accounting for future uncertainties in designing conservation areas. The tool is applicable to both spatial and non-spatial problems, such as budget allocation or species selection. Constraints for spatial design and spatial dependencies (e.g. connectivity among sites) can also be specified in SiteOpt. Users can optimize site selection based on two competing objectives by solving for the Nash bargaining solution. Importantly, by quantifying uncertainty and asset spatial correlation, a measure of risk can be included as one such objective to be traded off against portfolio benefits. Thus, SiteOpt can be used to explicitly manage risk in portfolio-based spatial optimization. This tool facilitates decisions in a variety of problem settings, including reserve selection, invasive species management, allocation of law enforcement activities for conservation, budget allocation and asset selection under uncertainty and risk.

Ecography↗

USGS2020

Spatial conservation planning under uncertainty using modern portfolio theory and nash bargaining solution

In recent years, researchers from interdisciplinary teams involving ecologists, economists and operations re- searchers collaborated to provide decision support tools to address the challenges of preserving biodiversity by optimizing the design of reserves. The goal of this paper is to further advance this area of research and provide new solutions to solve complex Spatial Conservation Planning (SCP) problems under uncertainty that consider risk preferences of decision makers. Our approach employs modern portfolio theory to address uncertainties in SCP problems, and involves two conflicting objectives: maximizing return and minimizing risk. We apply concepts from game theory such as the Nash bargaining solution to directly compute a desirable Pareto-optimal solution for the proposed bi-objective optimization formulation in natural resource management problems. We demonstrate with numerical examples that by directly computing a Nash bar- gaining solution, a Binary Quadratically Constrained Quadratic Program (BQCQP) can be solved. We show that our approach (implementable with commercial solvers such as CPLEX) can effectively solve the proposed BQCQP for much larger problems than previous approaches published in the ecological literature. Optimal solutions for problems with less than 400 parcels can be computed within a minute. Near optimal solutions (within at most 0.2% gap from an optimal solution) for high-dimensional problems involving up to 800 parcels can be computed within 8 hours on a standard computer. We have presented a new approach to solve SCP optimization problems while considering uncertainty and risk tolerance of decision makers. Our new approach expands considerably the applicability of such SCP optimization methods to address real conservation problems.

Ecological Modelling↗