Optimization models and methods for harvest planning and forest road upgrading
Abstract: The purpose of this thesis is to contribute to the development and the use of optimization models and methods to support efficient decision making in Swedish forestry. The main problem areas concerned are forest road upgrade planning and operational harvest planning. Today much of the planning is done manually by experienced managers. Forest management has a natural hierarchical structure based on the wide range of planning periods and organisational structure. The hierarchical harvest planning and the subdivision into strategic, tactical and operational levels are described from an Operations Research perspective. The description of the hierarchical structure differs between countries and there is a focus on the Swedish situation.Road upgrading is becoming an increasingly important planning problem to secure a continuous supply of wood. In Sweden, during the periods of thawing and periods of heavy rain there is an uncertain accessibility to parts of the road network due to unfirm ground. The thesis addresses the optimization problem to minimize the combined road upgrade and transportation costs while meeting requirements on road standard such that accessibility to harvest areas is secured during all weather conditions. In this work mixed integer linear programming (MILP) models including multiple assortments, several time periods and a set of road classes are developed. For a typical forest district, the road upgrade problem becomes large and techniques to improve solution performance through model reformulations are discussed. The models are tested in a case study for a major Swedish company. For practical usage of the models we present the development of a new decision support system called RoadOpt. The development has involved the Forestry Research Institute of Sweden, two software companies and several participating forest companies. The system uses a GIS-based map user-interface to present and analyse data and results. The recently developed Swedish road database is an important part. The system is tested on a case study from Stora Enso.The harvest planning problems addressed cover planning periods ranging from one year down to one month. Annual plans are required for budgeting, contracting harvest teams, contracting transportation firms and assuring road access. The main decisions deal with which areas to harvest, and by which team, during an annual period so that the industries receive the required volume of assortments. Overall decisions about transportation and storage are included. The monthly planning problem includes detailed scheduling of harvest crews, that is, the sequencing of areas for each team. The thesis addresses these planning problems and provides MILP models for each problem. Methods based on both a commercial solver and developed LP based heuristics are used. Models and methods are tested on case studies from Holmen Skog.
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