UBC Theses and Dissertations
Optimization of log logistics at the operational level considering sorting decisions and synchronization requirements Ghotb, Seyed Salar
Log logistics activities, such as transporting, loading/unloading, and processing of logs, are essential elements of forest operations and account for a significant portion of the total costs of delivered logs. Although previous studies investigated log logistics, they mainly emphasized on economic aspects and did not address some practical aspects of the logistics problem. The main goal of this dissertation is to optimize log logistics at the operational level incorporating practical considerations and complexities. In order to achieve this goal, a decomposition framework is employed that divides the log logistics problem into two phases. In the first phase, a bi-objective optimization model is developed in which sorting decisions, trucking contractors, and compatibility requirements at supply and demand locations are considered. The first objective of the bi-objective model is to minimize the total transportation costs, while the second objective addresses the social aspects by balancing the workload of contractors. The outputs of the first phase are used as the inputs of the second phase, for which an optimization model is developed to determine the daily routing and scheduling of heterogeneous trucks using continuous time representation. The model enables synchronization of log loaders and trucks and generates a detailed schedule of activities. In addition, a solution approach based on the simulated annealing algorithm is developed to solve the large-sized daily routing and scheduling problem. The Taguchi method is used to enhance the quality of the solutions by calibrating the input parameters of the algorithm. The framework, optimization models, and the solution approach are applied to a case study of a large Canadian forest company where logs are transported from cut blocks to sort yards for further processing. Results show that the framework can generate balanced workloads for all contractors with less than 1% increase in transportation costs and can determine the daily schedule of log trucks considering practical operational considerations. It is concluded that assigning overtime to trucks instead of dispatching a new truck can generate cost savings. The proposed models and the solution approach can be applied to other cases and regions by modifying the input data.
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