Search

This paper develops a simulation-based optimization supply chain model for supplying sawlogs to a sawmill from a forest management unit. The simulation model integrates the two-way flow of information and materials under the stochastic demand of the sawmill production unit. The dynamic optimization model finds the optimum inventory policy ( s, S) that minimizes the total inventory cost for the three supply chain agents - sawmill storage, merchandizing yard, and forest management unit. The model is used to analyze a real sawmill case study in northwestern Ontario, Canada. It was found that the merchandizing yard absorbs shocks of uncertain demand from the sawmill production unit and reduces idle time, but it increases the total cost of the supply chain by $11 802 (about 42%). The optimized model predicts that only 3.5 days of inventory is required at the sawmill storage. The simulation-based optimization supplier model will help in decision-making at the tactical and operational level in the forest products industry supply chain through a two-way flow of information and materials. [ABSTRACT FROM AUTHOR]

Developing a forest management plan in a multicriteria perspective is traditionally accomplished utilizing simulation and optimization tools as a means to predict and optimize a variety of criteria under consideration. Goal programming is a useful tool to balance conflicting aspects of the competing criteria. When information regarding an aspect of uncertainty is available, stochastic programming should be utilized to efficiently integrate this additional information. Research has been conducted into determining the accuracy of forest inventory methods; however, the measurement error is typically ignored when generating forest management plans. Through integrating the uncertainty in a systematic fashion, the forest management plan can be improved by describing the potential uncertainty in the plan and by managing the influences of this uncertainty. This paper develops three stochastic goal programming formulations and highlights the usefulness of the approach on a small forest holding. [ABSTRACT FROM AUTHOR]

Computer simulation is the only realistic method of evaluating alternative methods of breeding hybrid forest trees. Empirical tests would be very long term and expensive. This paper describes the development of a simulation program, called XSIM, which generates two different but closely related outcrossing tree species. The genetic correlation between performance in each parental species and performance in the resulting hybrid can be set, in addition to the amounts and types of variances in each parental species. The breeding strategies available for testing include conventional reciprocal recurrent selection, reciprocal recurrent selection with forward selection, recurrent selection within each pure species, and the creation of a synthetic species. XSIM allows the strategies to be compared using the same base populations, equivalent selection intensities, and comparable mating patterns. Innovative best linear unbiased prediction procedures allow all ancestral and current progeny generation data, from both parental species and the hybrid, to be analysed together. The theoretical basis for the simulation is given, and genetic and statistical models are described. In summary, XSIM allows rigorous comparisons of the strategies in terms of genetic gain per time and provides useful insight into hybrid forest tree breeding. [ABSTRACT FROM AUTHOR]