
This paper is concerned with a dynamic inventory control system described by a network model where the nodes are warehouses and the arcs represent production and distribution activities. We assume that an uncertain demand may take any value in an assigned interval and we allow that the system is disturbed by noise inputs. These assumptions yield a model with a mix of interval and stochastic demand uncertainties. We use the method of model predictive control to derive the control strategy. To deal with interval uncertainty we use the interval analysis tools and act according to the interval analysis theory. The developed results are illustrated using a numerical example.
управление цепями поставок, интервальный анализ, управление запасами, модельное прогнозное управление, многокритериальная оптимизация, квадратичное программирование, сетевые модели, интервально-стохастическая неопределенность
управление цепями поставок, интервальный анализ, управление запасами, модельное прогнозное управление, многокритериальная оптимизация, квадратичное программирование, сетевые модели, интервально-стохастическая неопределенность
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
