An improved scheme for accelerating the convergence of the simulated annealing algorithm applied to real world problems

When formulated in mathematical terms, the problem of zoning a protected natural area subject to both box and spatial constraints results in a large combinatorial optimization problem belonging to the NP-hard class. These facts suggest the need to apply a heuristic approach. In this contribution a new proposal to decrease the control parameter, known as temperature, in the simulated annealing algorithm is presented. The strategy is based on that proposed by Lundy and Mees [4], and developed in order to decrease the running time of the algorithm applied to large scale problems. When applied to solving small-size simulated problems, 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. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)