Particle Filtering Using Agent-based Transmission Models
Material requirements planning (MRP) is one of the main production planning approaches implemented in enterprise resource planning systems, and one that is broadly applied in practice. In this paper, a multi-stage and multi-item production system is simulated by considering random customers’ demands and other sources of uncertainty.
In this paper, researchers used a discrete event simulation to evaluate the performance of outlier correction methods and extended the forecast generation process to increase forecast accuracy.
Physical distancing is recommended as the most efficient strategy for defending individuals from long-term global pandemics. It lowers the risk of community spreading, especially for indoor spaces. This paper aims to model physical-distancing behaviors in an educational facility, using agent-based simulation, and evaluate the impact of measures (e.g., controlling classroom capacity, breaktime scheduling) on physical distance violation risks.
Operational controllers are a critical component for smart factories and the realization of initiatives like Industry 4.0, where good reliable operational decision-making is critical to success. The contribution of this paper is providing a concrete example of an operational controller that conforms to ISA-95, embodies the necessary computational decision making to be considered 'smart' and has a plausible path to implementation.
This article introduces an innovative approach of risk and opportunity management to help managers in their decision-making processes. The proposed “physics of decision” approach enables managers to deal with the considered system’s performance trajectory by viewing and assessing the impact of potentialities (risks and opportunities).
The storage of electrical energy is becoming increasingly important to satisfy the demand through renewable energy sources. In this paper, a continuous and discrete simulation of a pumped thermal energy storage (PTES) system are compared with respect to their computational time and accuracy.
The COVID-19 pandemic is an unprecedented public health and economic crisis, that dramatically impacted different industries, and presented an unforeseen challenge to the automotive industry and its supply chain. Researchers modeled a system dynamics simulation to demonstrate the behavior of a multi-echelon supply chain responding to different end market scenarios.
This paper provides an overview of revenue management characteristics and methods in the semiconductor industry in order to enable greater customer satisfaction and supply chain flexibility while increasing revenue.