A test of knowledge-based forest operations scheduling procedures

Abstract

Five knowledge-based approaches (three search routines and two expert systems) to forest operations scheduling were compared with mathematical programming (linear programming and mixed integer programming) and simulation approaches for two plantation forests in New South Wales, Australia. Strategies produced using these approaches were compared on the basis of scores for timber volume flow, scenic beauty, stand health, and water quality. Timber flow scores were highest for the linear programming strategies, but some of the strategies produced by the knowledge-based approaches scored almost as high. The timber flow scores for the mixed integer programming strategies were exceeded by some of the knowledge-based strategies, because of the approximations required to achieve mixed integer programming solutions for larger problems. The knowledge-based approaches could produce higher scoring strategies for the other criteria than the mathematical programming or simulation approaches. The multiple strategies produced by two of the search procedures, and the goal hierarchy incorporated into the expert systems, allow the user to make explicit trade-offs among strategies in terms of performance for the various criteria.