Quarterly Journal of International Agriculture No. 3/13
Approximating Optimal Numerical Solutions to
Bio-economic Systems:
How Useful is Simulation-optimization?
Jan Börner
University of Bonn, Germany
Steven I. Higgins
University of Otago, Dunedin, New Zealand
Simon Scheiter
Frankfurt University, Frankfurt/Main, Germany
Jochen Kantelhardt
University of Natural Resources and Life Sciences, Vienna, Austria
Abstract
For applications in agricultural and environmental economics, complex ecological
systems are often oversimplified to the extent that ecologists rarely consider model
results valid. Recursive optimization of complex systems represents an alternative, but
requires strong assumptions regarding time preference and uncertainty. In this paper
we explore the implications of merely approximating “true” optima of complex
dynamic optimization problems using a technique called simulation-optimization. We
develop a standard discrete renewable resource use problem and solve it numerically
using both simulation-optimization and non-linear mathematical programming. We subsequently
introduce non-linearity and uncertainty and graphically compare the performance
of simulation-optimization vis-à-vis non-linear programming in predicting
optimal control and state variable paths. On the basis of this comparison we discuss
potential non-formal test procedures that could be used to assess simulation-optimization
solutions of more complex problems that do not allow for such comparisons. We
find that simulation-optimization can be a useful exploratory optimization technique
when standard numerical optimization approaches fail to find near optimal solutions.
That said, modelers should be careful in designing management functions of simulationoptimization
problems and test their functional forms for severe misspecifications.
Keywords: renewable natural resource management, rangeland, optimal control, complex systems
JEL: Q570
Vol. 52 (2013), No. 3: 179-198