The aim of this paper is to describe a methodology that has been used to assist in formulating sound production and marketing plans for a forest enterprise by relating information on stem frequency, size, and defect collected in routine inventories of forest resources to the projected demand for various log types. Emphasis is given to efficient bucking on landings of resources that are to be felled within a planning period as a whole, rather than efficient prescriptions for either each stand or each individual stem. The central model is a Dantzig–Wolfe decomposition procedure with a linear programming master and dynamic programming subproblems. The dynamic programming algorithm is used to maximize return from bucking a sequence of logs from single stems. From a set of alternative bucking patterns for different stem classes, the linear program selects those that maximize overall financial return, subject to satisfying constraints on resource availability and for a mix of log types from which end-use product demands can be met. Informational requirements for and applications of the model are presented with reference to a plantation resource of Caribbean pine belonging to the Fiji Pine Commission.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.