Abstract
This study investigates the dynamic performance and optimization of a typical discrete production control system under supply disruption and demand uncertainty. Two different types of uncertain demands, disrupted demand with a step change in demand and random demand, are considered. We find that, under demand disruption, the system’s dynamic performance indicators (the peak values of the order rate, production completion rate, and inventory) increase with the duration of supply disruption; however, they increase and decrease sequentially with the supply disruption start time. This change tendency differs from the finding that each kind of peak is independent of the supply disruption start time under no demand disruption. We also find that, under random demand, the dynamic performance indicators (Bullwhip and variance amplification of inventory relative to demand) increase with the disruption duration, but they have a decreasing tendency as demand variance increases. In order to design an adaptive system, we propose a genetic algorithm that minimizes the respective objective function on the system’s dynamic performance indicators via choosing appropriate system parameters. It is shown that the optimal parameter choices relate closely to the supply disruption start time and duration under disrupted demand and to the supply disruption duration under random demand.
Highlights
Recent years have witnessed various unforeseen disasters, such as terrorist acts, accidents, and natural calamities, implying that our world is becoming increasingly fragile and uncertain
The combined impacts of supply and demand uncertainties on the dynamic performance of production control systems have been generally overlooked by the literature. This ignorance may cause a firm to significantly underestimate the negative effect of multiple sources of uncertainties and to undertake remarkable excessive production and inventory carrying costs. By incorporating both supply disruption and demand uncertainty, this study investigates the dynamic performance of a typical production control system
This study investigates the dynamic performance of the APIOBPCS and the optimization of the system in the presence of supply disruption and demand uncertainty
Summary
Recent years have witnessed various unforeseen disasters, such as terrorist acts, accidents, and natural calamities (e.g., earthquakes, floods, and hurricanes), implying that our world is becoming increasingly fragile and uncertain. The combined impacts of supply and demand uncertainties on the dynamic performance of production control systems have been generally overlooked by the literature This ignorance may cause a firm to significantly underestimate the negative effect of multiple sources of uncertainties and to undertake remarkable excessive production and inventory carrying costs. In the case of demand disruption, a step change in demand occurs in the beginning of the simulation time horizon, and we adopt the peaks of the order rate, production completion rate, and inventory level as the main dynamic performance indicators. Under the case of demand disruption, the weighted sum of the order rate peak and inventory peak is adopted as the objective function to minimize We discover that both the supply disruption duration and start time have significant impacts on the selected optimal parameters.
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