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The use of relaxation to solve harvest scheduling problems with flow, wildlife habitat, and adjacency constraints Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/wm117s078

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  • Lagrangean relaxation is presented as a solution technique to solve flow constrained area-based harvest scheduling problems. The best set of multipliers in the Lagrangean approach is obtained through the subgradient method. Guidelines to set some parameters to compute the step size in the subgradient algorithm are provided. An additional procedure to improve the multipliers obtained through the subgradient algorithm is provided. The area-based harvest scheduling problem with adjacency constraints is approached by reducing the number of these constraints required to specify the adjacency relations among harvest units. A heuristic procedure is proposed to to perform this reduction. Such a procedure is based on computing one adjacency constraint per harvest unit. Additional reductions are possible by eliminating the harvest units whose adjacency relations are described by surrounding areas. By using surrogate relaxation the set of adjacency constraints is reduced to one constraint, Combining Lagrangean and surrogate relaxation the area-based harvest scheduling problem with adjacency constraints can be further reduced, so the relaxed problem becomes easier to solve than the original problem. The relaxation approach is used to solve the habitat dispersion problem. Simulated examples show that simultaneously optimizing flow, wildlife and adjacency constraints within an area-based approach will be costlier than previous continuous models have led us to believe.
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