Browsing by Author "Nelson, John D."
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Item A Robust Model for Protecting Road-Building and Harvest-Scheduling Decisions from Timber Estimate Errors(2014) Palma, Cristian D.; Nelson, John D.Road-building and harvest-scheduling decisions are primarily based on timber estimates and forecasts that are known to contain errors. It has been shown that in the presence of constraints, decisions generated under these conditions are likely to become infeasible. Therefore, solutions are required that can ensure constraint fulfillment despite the estimation errors. We present a robust model formulation of a multiperiod road-building and harvest-scheduling problem in which protection against minimum demand infeasibility is sought despite the existence of timber estimates that are defined as continuous ranges of values instead of point estimates (as is usually the case in this type of problems). We compare the benefits of this robust formulation with those of the traditional deterministic option and explore the tradeoff between the robustness of the solutions and its impact on the objective function. By simulating different scenarios of the timber coefficient realizations, it is shown that the robust approach produces solutions that are less sensitive to errors in the timber estimates at the expense of a slight reduction in the objective function.Publication Assessing the effectiveness of static heuristics for scheduling lumber orders in the sawmilling production process(2024) Vergara, Francisco P.; Palma, Cristian D.; Nelson, John D.Although optimization models can be used to plan the production process, in most cases static heuristics, such as earliest due date (E), longest processing time (L), and shortest processing time (S), are used because of their simplicity. This study aims to analyze the production cost of the static heuristics and to determine how this cost relates to the size of the production orders in the sawmilling industry. We set a planning problem with different orders and due dates and solved it using two cost-minimization models to compare their solutions. The first was a planning model (PL) where orders were split up into products demand by period, and the second, a planning scheduling (PS) where the sequence of processing orders based on static heuristics was assumed as known. In the latter, the minimum production cost for each static heuristic was found. In both models, the same resource constraints were assumed. The costs showed no significant changes based on order sizes. However, 0,5 % of orders were delayed using PS-E, and 17 % of orders were delayed using PL. PL was an efficient solution method when changing the orders´ size and when looking for the best static heuristic to process the orders. However, PS-E showed the ability to reduce the backlog close to zero while the PL backlog ratio was 17 %. No penalties were applied to backlogs due to their subjective nature; however, when shortages occurred, the demand was unmet or backlogged with substantial costs. Thus, in case the proposed method is adopted using a conservative backlog cost, a sawmill producing under the cut-to-order environment that produces 300000 m3 /year would reduce backlogged orders by 51000 m3. If the holding lumber cost is 2 $/m3, annual savings would be $408000.Item Modeling Lean and Agile Approaches: A Western Canadian Forest Company Case Study(01/09/2018) Vergara, Francisco P; Palma, Cristian D.; Nelson, John D.In the forest supply chain of the coast of British Columbia, the material flows are directed toward the push production of commodity products. This industry has not adopted lean and agile principles due to unclear economic impacts on the supply chain in changing market conditions. We tested the ability of lean and agile principles to improve performance in the coastal integrated forest industry. Mixed integer programming formulations were subject to over-under production capacity, and over-under demand fulfillment penalties to emulate agile, lean, and hybrid manufacturing environments, when solving the planning problem. Assuming that the coastal integrated forest industry performs as a hybrid environment, the profit results of each manufacturing environment were judged. The results show that, opportunities for profit improvement were 11% for adopting an agile environment when demand was stable with low variation and large batches of production. However, profit improvement was non-existent when the same demand attributes apply but with high variation. The opportunities for profit improvement were 12% when an agile environment or lean environment was adopted when demand was stable with low variation and small batches of production. However, opportunities for profit improvements of 15% existed for adopting an agile environment when demand was unstable with high variation and small batches of production