Abstract

Multi period linear programming with integer and quadratic generalizations, have often been used to optimise forest level scheduling under constraints. Then, stochastic markets and environmental conditions have usually been neglected. Adaptive decisions and sequential information concerning changes of exogenous stochastic variables have sometimes been considered in stand analysis. Then, higher level constraints have not been considered. This paper contains definitions and preliminary analyses of typical adaptive real world harvest scheduling problems at forest properties with stochastic markets. Adaptive approaches from stochastic scenario optimisation and from stochastic dynamic programming are used and compared

Published in

New Opportunities for Operations Research
2003, volume: 2003
Publisher: INFORMS

Conference

New Opportunities for Operations Resear

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