MODELING OF OPERATING PROCEDURES IN A FOREST COMPARTMENT UNDER FUZZY DYNAMIC NATURE WORKING CONDITIONS
Abstract
In this paper the principles and calculations of stretched in time graphic-analytical models of the operating network are proposed. They allow you to determine the sequence of logging operations at logging sites within the forest compartment, to reduce nonmechanical delay and increase technological efficiency of harvesting operations with fuzzy dynamic natural-production conditions. Search algorithm minimal cost flow developed to solve the proposed graphic-analytical model. It allows to justify the amount of expenses and calculate a maximum bandwidth of arcs between the fictitious source and drain of graphical model. The model differs complex use of two main characteristics of the process of logging operations: productivity and labor costs are presented as individual capacities of graph arcs.
In order to solve the suggested graphic model, we developed the search algorithm of minimum cost flux, providing grounds for the typical expenditures and calculating the carrying capacity between the false source and runoff within the structure of suggested graphic models, different in two core characteristics of the logging process: productivity and labour inputs, represented as the carrying capacity of the graph arcs. The suggested graphical-analytic approach represents a certain task type of graph theory, according to which the transportation of flux along the dynamic operational network arcs reduces their carrying capacity. Every arc denotes analogous technological operations within the analysed time period. This is the distinctive feature of the suggested approach.
The suggested design and calculation principles for time expanded graphical-analytical models of the operational network enable to provide rationale for the logging consequence and technological operations in fuzzy dynamic nature environment of a forest compartment, reduce operational downtime and enhance the efficiency of forest harvesting operations.
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