Harvest scheduling with spatial constraints: a simulated annealing approach

Abstract

Simulated annealing is a stochastic approach to solving large combinatorial problems. This approach was used to model a harvest scheduling problem having block size constraints (no limit, 100–200, and 200–400 ha), a 20-year adjacency delay, and objectives to meet harvest volume targets on the minimum area possible. Spatially explicit harvest schedules complying with the constraints were successfully generated on test data sets of 6148 and 27 548 forest stands.