The article contains formulation of the task of wood harvesting machines scheduling, including distribution of machines over the sites, scheduled for harvesting during the planning period, taking into account delivery schedules for each type of products, as well as various technical and technological constraints. A mathematical model of the problem is developed and a numerical solution method is proposed. The method is based on application of the meta-heuristic algorithm of simulated annealing and "greedy" algorithms. Comparison of several variants of the algorithm for solving this problem was made. The method applying spatial clustering of harvesting sites has been recognized as the most effective one. Approbation of the algorithm using real data has confirmed the possibility of reducing the costs of forest machines relocation while meeting all technological requirements. The scientific results presented in the article were used in the software system Opti-Wood for wood harvesting planning and management, developed by Opti-Soft company.
This paper describes an approach to the optimal planning of wood harvesting and timber supply for forest companies of Russia. Software and tools successfully used in other countries (e.g., Finland, Sweden, Canada, etc.) are not as effective in Russian conditions for a number of reasons. This calls for the development of an original approach to solve this problem with respect to Russia’s specific conditions. The main factors affecting the operation of wood harvesting companies in Russia were determined. The optimization problem was formulated taking into account all important features of wood harvesting specific to the country. The mathematical model of the problem was formulated and analyzed. An important requirement is that the solution algorithm should find high-quality plans within short computation times. The original problem was reduced to a block linear programming problem of large dimension, for which an effective numerical solution method was proposed. It is based on the multiplicative simplex method with column generation within Dantzig–Wolfe decomposition and uses heuristics to determine feasible solutions based on the branch and bound method. We tested the solution approach on real production data from a forest company in southern Karelia with a planning horizon up to a year. This case study involved 198 sites and 14 machines harvesting up to 200,000 cubic meters from an available stock volume of about 300,000 cubic meters. An increase in profit by 5% to 10% was observed, measured as revenue from the sale of products, net of harvesting and transportation costs.
An approach to the optimal timber transport scheduling is described in the paper. A description of this problem is given, a multi-criteria mathematical model is created. It is noted that the problem belongs to the class of General vehicle routing problems (GVRP) associated with the job-shop scheduling. A hybrid algorithm for solving this problem based on the decomposition method using the simplex method and the genetic algorithm is developed. Testing of the proposed approach using real data from wood harvesting enterprises showed its effectiveness. The algorithm was implemented in “Opti-Wood” decision support system for wood harvesting planning and management, developed by Opti-Soft company (Russia).
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