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Goal programming in forest management: customising models for the decision-maker's preferences

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.