Current issue: 54(4)
Under compilation: 54(5)
Linear optimization model was used to calculate seven wood procurement scenarios for years 1990, 2000 and 2010. Productivity and cost functions for seven cutting, five terrain transport, three long distance transport and various work supervision and scaling methods were calculated from available work study reports. All methods are based on Nordic cut to length conditions. Finland was divided in three parts for description on harvesting conditions. Twenty imaginary wood processing points and their wood procurement areas were created for these areas. The procurement systems, which consists of the harvesting conditions and work productivity function, were described as a simulation model. In the LP-model the wood procurement system has to fulfil the volume and wood assortment requirements of processing points by minimizing the procurement cost. The model consists of 862 variables and 560 restrictions.
Results show that it is economical to increase the mechanical work in harvesting. Cost increment alternatives effect only little on profitability of manual work. The areas of later thinnings and seed tree- and shelterwood cuttings increase on cost of first thinnings. In mechanized work one method, 10-tonne one grip harvester and forwarder, is gaining advantage among other methods. Working hours of forwarder are decreasing opposite to the harverster. There is only little need to increase the number of harvesters and trucks or their drivers from today’s level. Quite large fluctuations in level of procurement and cost can be handled by constant number of machines, by alternating the number of season workers and by driving machines in two shifts. It is possible, if some environmental problems of large-scale summer time harvesting can be solved.
The applicability of five mathematical programming methods, namely standard linear programming, parametric programming, goal programming, mixed integer programming and integer programming is discussed as a planning tool for the choice of wood procurement method.
Theoretically, the goal programming approach seems to be the best routine for mathematical handling of problems related to wood procurement. The parametric approach must include enough large post-optimality analysis routine. If the effect of the variables expressed with different measures is to be studied, interpretation of the economic information given by the approach becomes a problem. The other drawback is that the approach does not allow determination of the hierarchy of the goals objectively as they depend on the subjective preferences of the decision maker.
From the practical point of view, standard linear programming is the best method if the objective function can be formulated in economic terms, for instance. If there are several goals to be attained or satisfied the best method is goal programming.
According to the sub-studies, every method under consideration can be used as a solution routine for the minimization of wood procurement costs. In cost minimization the best methods are goal programming and standard linear programming. The best method for harvesting system evaluation purposes is parametric because it allows varied cost calculations within a certain cost range. The best method for harvesting equipment investment planning is mixed integer programming with binary decision variables.
The more complicated and restricted the problem environment is, the better the mathematical programming approach will be, also in harvesting related problems.
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