Scheduling of log logistics using a metaheuristic approach

An efficient log logistics plan results in log procurement cost savings. In practice, log logistics presents complexities such as synchronization of different machines, sorting of logs, and compatibility requirements. To address these complexities, this research proposes a decomposition approach for optimization of log logistics considering synchronization of log loaders and heterogeneous trucks at both cut blocks and sort yards. In the first phase, the daily number of truckloads between cut blocks and sort yards for each trucking contractor is determined, while allocation of the truckloads to compatible trucks and detailed routing and scheduling decisions are addressed in the second phase. Furthermore, a simulated annealing algorithm is developed for the second phase to obtain the schedules for large-sized problems. Additionally, the parameters of the algorithm are tuned using the Taguchi method. The algorithm is then applied to a case of a large Canadian forest company in British Columbia, Canada with a 1-month planning horizon. The results show that the proposed solution approach can successfully satisfy synchronization requirements and generate detailed schedules in a reasonable time. Also, cost savings for contractors are possible by assigning overtime rather than utilizing more trucks to fulfill their transportation tasks.