When formulated in mathematical terms, the problem of zoning a protected natural area subject to both box and spatial constraints results in a combinatorial optimization problem belonging to the NP‐hard class. This fact and the usual dimension of the problem (regularly in the tens of thousands order) suggest the need to apply a heuristic approach. In this contribution we describe a quantitative method for zoning protected natural areas based on a simulated annealing algorithm. Building upon previous work by Bos (1993), we introduce three main innovations (a quadratic function of distance between land units, a non‐symmetric matrix of compatibilities among uses, and a spatial connection constraint) that make the approach applicable for ecological purposes. When applied to solving small‐size simulated problems, the results were indistinguishable from those obtained via an exact, enumerative method. A coarse‐scale zoning of Talampaya National Park (Argentina) rendered maps remarkably similar to those produced by subject area experts using a non‐quantitative consensus‐seeking approach. Results are encouraging and show particular potential for the periodical update of zoning of protected natural areas. Such a capability is crucial for application in developing countries where both human and financial resources are usually scarce but still critical for updating zoning and management plans.

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María F. Natale -Domingo A. Tarzia, "An integral equation in order to solve a one-phase Stefan problem with nonlinear thermal conductivity", 15-24.María C. Sanziel -Domingo A. Tarzia, "Optimization on the heat flux in a mixed elliptic problem with temperature constraints", 25-30.Claudia M. Gariboldi -Domingo A. Tarzia, "A new proof of the convergence of distributed optimal controls on the internal energy in mixed elliptic problems", 31-42.