Rene Zamora-Cristales, Kevin Boston, John Sessions, Glen Murphy. (2013). Stochastic simulation and optimization of mobile chipping economics in processing and transport of forest biomass from residues. Silva Fennica vol. 47 no. 5 article id 937. https://doi.org/10.14214/sf.937

Keywords: forest planning; simulation; optimization; economics; decision analysis; forest biomass; renewable energy

Highlights: A stochastic simulation model is proposed to analyze forest biomass operations; The cost of chipper and truck waiting times was estimated in forest biomass recovery operations; The economic effect of truck-machine interactions under uncertainty was analyzed; Road characteristics and processing location have an economic impact in truck and chipper waiting times

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We analyzed the economics of mobile chipping and transport of biomass from forest residues for energy purposes under uncertainty. A discrete-event simulation model was developed and utilized to quantify the impacts of controllable and environmental variables on productivity in order to determine the most cost effective transportation options under steep terrain conditions. Truck-chipper interactions were analyzed to show their effect on truck and chipper standing time. A costing model was developed to account for operating and standing time cost (for the chipper and trucks). The model used information from time studies of each activity in the productive cycle and spatial-temporal information obtained from geographic information system (GIS) devices, and tracking analysis of machine and truck movements. The model was validated in field operations, and proved to be accurate in providing the expected productivity. A cost distribution was elaborated to support operational decisions of forest managers, landowners and risk-averse contractors. Different scenarios were developed to illustrate the economic effects due to changes in road characteristics such as in-highway transport distance, in-forest internal road distance and pile to trailer chipper traveling distances.

Zamora-Cristales, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: rene.zamora@oregonstate.edu
Boston, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: kevin.boston@oregonstate.edu
Sessions, Department of Forest Engineering, Resources, and Management, College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA E-mail: john.sessions@oregonstate.edu
Murphy, Waiariki Institute of Technology, Rotorua, New Zealand E-mail: glen.murphy@waiariki.ac.nz

article id 357, category Research article

Elizabeth Dodson Coulter, John Sessions, Michael G. Wing. (2006). Scheduling forest road maintenance using the analytic hierarchy process and heuristics. Silva Fennica vol. 40 no. 1 article id 357. https://doi.org/10.14214/sf.357

Keywords: decision support; simulated annealing; threshold accepting; road environmental impacts; AHP

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The management of low-volume roads has transitioned from focusing on maintenance designed to protect a capital investment in road infrastructure to also include environmental effects. In this study, two models using mathematical programming are applied to schedule forest road maintenance and upgrade activities involving non-monetary benefits. Model I uses a linear objective function formulation that maximizes benefit subject to budgetary constraints. Model II uses a non-linear objective function to maximize the sum of benefits divided by the sum of all costs in a period. Because of the non-linearity of the constraints and the requirements that the decision variables be binary, the solutions to both problem formulations are found using two heuristics, simulated annealing and threshold accepting. Simulated annealing was found to produce superior solutions as compared to threshold accepting. The potential benefit for completing a given road maintenance or upgrade project is determined using the Analytic Hierarchy Process (AHP), a multi-criterion decision analysis technique. This measure of benefit is combined with the economic cost of completing a given project to schedule maintenance and upgrade activities for 225 km (140 miles) of road in forested road systems within western Oregon. This combination of heuristics, cost-benefit analysis, environmental impacts, and expert judgment produces a road management schedule that better fits the current road management paradigm.

Coulter, College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA E-mail: elizabeth.coulter@cfc.umt.edu
Sessions, Department of Forest Engineering, College of Forestry, Oregon State University, 204 Peavy Hall, Corvallis, OR 97331-5706, USA E-mail: js@nn.us
Wing, Department of Forest Engineering, College of Forestry, Oregon State University, 204 Peavy Hall, Corvallis, OR 97331-5706, USA E-mail: mgw@nn.us

article id 545, category Research article

Pete Bettinger, David Graetz, Kevin Boston, John Sessions, Woodam Chung. (2002). Eight heuristic planning techniques applied to three increasingly difficult wildlife planning problems. Silva Fennica vol. 36 no. 2 article id 545. https://doi.org/10.14214/sf.545

Keywords: forest planning; spatial harvest scheduling; adjacency constraints

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As both spatial and temporal characteristics of desired future conditions are becoming important measures of forest plan success, forest plans and forest planning goals are becoming complex. Heuristic techniques are becoming popular for developing alternative forest plans that include spatial constraints. Eight types of heuristic planning techniques were applied to three increasingly difficult forest planning problems where the objective function sought to maximize the amount of land in certain types of wildlife habitat. The goal of this research was to understand the relative challenges and opportunities each technique presents when more complex difficult goals are desired. The eight heuristic techniques were random search, simulated annealing, great deluge, threshold accepting, tabu search with 1-opt moves, tabu search with 1-opt and 2-opt moves, genetic algorithm, and a hybrid tabu search / genetic algorithm search process. While our results should not be viewed as universal truths, we determined that for the problems we examined, there were three classes of techniques: very good (simulated annealing, threshold accepting, great deluge, tabu search with 1-opt and 2-opt moves, and tabu search / genetic algorithm), adequate (tabu search with 1-opt moves, genetic algorithm), and less than adequate (random search). The relative advantages in terms of solution time and complexity of programming code are discussed and should provide planners and researchers a guide to help match the appropriate technique to their planning problem. The hypothetical landscape model used to evaluate the techniques can also be used by others to further compare their techniques to the ones described here.

Bettinger, Department of Forest Resources, Oregon State University, Corvallis, OR 97331 E-mail: pete.bettinger@orst.edu
Graetz, Department of Forest Resources, Oregon State University, Corvallis, OR 97331 E-mail: dgw@nn.us
Boston, Carter Holt Harvey Forest Fibre Solutions, Tokoroa, New Zealand E-mail: kb@nn.nz
Sessions, Department of Forest Engineering, Oregon State University, Corvallis, OR 97331 E-mail: js@nn.us
Chung, Department of Forest Engineering, Oregon State University, Corvallis, OR 97331 E-mail: wc@nn.us

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