3-level MCGP: an efficient algorithm for MCGP in solving multi-forest management problems

Abstract

Multi-use forest planning is not an easy task for forest managers because of the difficulty in defining a clear set of competing goals. Multi-choice goal programming (MCGP) can get an ideal solution more quickly for the multi-use forest problems by setting various target goal values for each goal. However, decision-makers may miss a better one if the set of target goal values are far from the best ideal solution. The purpose of this paper is to propose a new algorithm (3-level MCGP) which can complete the insufficiency of the MCGP technique by combining binary search algorithm to reduce the number of comparison in MCGP method and then achieve the best ideal solution as close as possible. Building on the results of a published case by goal programming (GP), this paper demonstrates that a more favorable alternative could be discovered by the new algorithm in a few steps. Through the re-allocation of forestland by the 3-level MCGP, forest managers can increase preferred forest production without losing the other minor production. The results of this study also indicated that, the 3-level MCGP is an efficient technique that can help forest managers to obtain an appropriate resource allocation and even achieve more forest production.