Optimization of Wood Supply: The Forestry Routing Optimization Model
Fuzzy Sets; Fuzzy Control; Decision Making; Logistics; Timber Trucking
In order to maximize the fleet of vehicles and cranes while taking operational limits into account, the focus of this work is on developing and evaluating a controlling device for timber logistics. To determine prospective wait times for the optimized system, a queue simulator is used. One scenario includes the controlling device, whereas the other does not. The study emphasizes the benefits of vehicle type A, which has more wheelers and fewer cranes than vehicle type B, making it more effective at constructing a queuing system. Although a numerical analysis is not given, the use of fewer cranes also suggests possible cost reductions. The Forest Transportation Problem model was used by the researchers to optimize the placement of trucks and cranes during loading and unloading operations. This model’s concise mathematical formulation made it effective and easy to use. The fuzzy controlling device (FCD), which simulates human decision-making in allocating wheelers to cranes, improves understanding of the optimization outcomes. When comparing sce- nario 2 with it to scenario 1 without it, the latter seems to be more beneficial in replicating the queuing system for the particular study situation. In the forest transportation scheme, the com- bination of FCD and the queue simulator provides logical behavior of queues. The study findings show how the created controlling device may effectively optimize timber logistics, resulting in in- creased queuing system efficacy and potential crane utilization cost savings. The FCD application improves decision-making and offers insightful information on forest transportation operations.