Eight Heuristic Planning Techniques Applied to Three Increasingly Difficult Wildlife Planning Problems: A Summary

Abstract

Forest planning goals are becoming increasing complex, as both spatial and temporal characteristics of desired future conditions are becoming important measures of forest plan success. Eight types of heuristic planning techniques were applied to three increasingly difficult forest planning problems where the objective function sought to maximize the amount of land in certain types of wildlife habitat. The eight heuristic techniques were random search, simulated annealing, great deluge, threshold accepting, tabu search with 1-opt moves, tabu search with 1-opt and 2-opt moves, genetic algorithm, and a hybrid tabu search / genetic algorithm search process. Three classes of techniques were determined: very good (simulated annealing, threshold accepting, great deluge, tabu search with 1-opt and 2-opt moves, and tabu search / genetic algorithm), adequate (tabu search with 1-opt moves, genetic algorithm), and less than adequate (random search). The data sets are available on the WEB.