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Abstract
Within a multi-criteria perspective goal programming (GP) is the most widely used approach for addressing forest management problems of a continuous nature. A key element of a GP model is the achievement function. Each type of achievement function is supported by a very precise structure of decision-makers' preferences. However, in many of the GP applications reported in the forest management literature, the achievement function of the GP model is chosen without justifying the reasons for its election. However, the right election of a GP achievement function is a crucial matter if we want the GP model to capture the essential features of the forest management reality analysed. In coherence with these ideas, this article aims: (1) to provide a precise preferential interpretation of the different GP achievement functions and (2) to provide some insight and guidelines about how to choose the most suitable GP achievement function for a precise forest resource management problem. Hopefully the ideas presented in this article will help to forest management analysts in the design of GP models that reflect with enough accuracy the preferences of the decision-maker.
Acknowledgements
A preliminary version of this article was presented at the 14th Symposium for Systems Analysis in Forest Resources (SSAFR 2011), held in Maitencillo (Chile) in March 2011 and at the Workshop “Methods and Tools for Participatory and Adaptive Forest Management Planning”, held in Fez (Morocco) in December 2011. This research has been funded by the Spanish Ministry of Economy and Competitiveness under project AGL2011-25825 and by the Government of the Madrid Autonomous Region. Comments and suggestions raised by the editor and by two referees have greatly improved the presentation and accuracy of the paper. Thanks are given to Diana Badder for her English editing.
