STATISTICAL SIMULATION AND TIME MANAGEMENT IN PROJECTS WITH TURBULENT ENVIRONMENT

Abstract

The peculiarities of the influence of turbulent projects environment on the start-up time and duration of works in sugar beet harvesting projects are revealed. In particular, the influence of two probabilistic components of the project environment is considered – agrometeorological and subject-biological. It is shown how the use of the Monte Carlo method (statistical simulation) allows to take into account the combined influence of uncontrolled and stochastic components of the turbulent projects environment on the timeliness of work in projects and the effectiveness of their implementation. The main indicators that should be taken into account in the statistical simulation model of projects are revealed to establish the characteristics of the natural start time of projects and duration of work, as well as to determine their timeliness. Emphasis is placed on the fact that the use of statistical simulation methods allows to perform multiple implementations (iterations) of the virtual project model. On this basis, the turbulence of the project environment and its impact on the work timeliness are reproduced and performance indicators of relevant projects. The results of computer experiments with a statistical simulation model on the influence of turbulent design environment on the timing of work in projects are processed and summarized. Distributions of naturally determined start-up time of sugar beet harvesting projects with different planned duration of works have been established. Differential functions of distribution and estimation of statistical characteristics of naturally determined start-up time of sugar beet harvesting projects are given. Integral dependences of distribution of naturally caused start-up time of projects on various planned duration of their implementation are constructed. The dependence of estimates of the mathematical expectation of the naturally determined start-up time of sugar beet harvesting projects on the planned duration of their implementation is established. The urgency of the task and the practical possibility of creating methods and models for time management in harvesting projects, and thus the development of automated decision support systems to improve the efficiency of these projects management.