Model III : a sequential approach to joint optimization of the stand treatment and forest level harvest scheduling problem Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/dj52w7538

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  • Harvest scheduling and stand level optimization have generally been regarded as separable problems. Some studies have attempted to jointly optimize a wide range of stand treatments and a forest wide harvest schedule using combinations of mathematical programming techniques. The mathematical programming forest level techniques presume perfect information on production, costs and revenues over long sequences of planning periods and simultaneously optimize harvest for all periods in the planning horizon using assumed perfect knowledge of intertemporal trade-offs. This study proceeds from a completely different behavioral basis, assuming that stand level planning and harvest scheduling proceed sequentially rather than simultaneously over every period. The full array of stand-age types and management regimes is optimized using backwards recursive dynamic programming. This defines an optimal treatment for the current period and a projected set of treatments for harvest and regeneration for each stand in the forest. The discounted present net value of each potential treatment for each stand in the current period is calculated and provided to the harvest scheduling portion of the model. The highest valued treatment from each stand constitutes the set of treatments that will be applied if there are no harvest volume constraints or if the indicated harvest is within specified volume limits. Otherwise, suboptimal stand treatments are ranked in order of increasing opportunity costs for increasing or decreasing harvest and the limit or constraint is met at minimum opportunity cost by altering sufficient stand treatments. An option of the model with harvest constraints met only at a maximum specified opportunity cost is also demonstrated. The stand-level optimization is repeated for each period in the planning horizon using new price and cost information.
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