Explore an advanced approach to vehicle routing optimization that combines simulation modeling with real-world road networks. This method addresses the Multi-Depot Vehicle Routing Problem (MDVRP) using AnyLogic.
This paper presents a framework that combines simulation with mathematical optimization to plan the supply of raw materials for producing specialty chemicals. A real-world use case was introduced to validate the developed framework, demonstrating the application of simulation in chemical industry logistics.
The study explores the critical need to address vulnerabilities within the semiconductor supply chain, given its global network and production timelines. It showcases the application of system dynamics simulation through AnyLogic software. The researchers assess the impacts of external disruptions and observe the change in customer orders, revenue, and distribution center stock in different operational strategies for managing supply chain disruptions.
Blood supply chains are an essential element of healthcare systems. Simulation provides the means to test out digital innovations for blood supply chains regarding their operational efficiency and expected costs.
The bullwhip effect, a phenomenon of progressively larger distortion of demands across a supply chain, can cause chaos and disorder with amplified supply and demand misalignment. An agent-based simulation model was developed to evaluate how risk pooling and information sharing between distinct entities in a supply chain can reduce the bullwhip effects. In agent-based paradigm different components of a system were described as agents which interact with each other in an environment.
This paper introduces a simulation study of interventions to ensure a stable supply of a generic medicine in Norway. A hybrid simulation modeling framework is proposed to evaluate the effect of alternative supply chain shortage interventions in response to various disruptions to support national decision making with respect to preparedness planning and emergency response.
Urban logistics is becoming increasingly important due to the global rise of e-commerce with home deliveries of small but frequent orders from consumers. The introduction of self-collection delivery systems is an innovation for last mile delivery operations in urban areas and brings new benefits. This paper introduces the application of hybrid modeling approach for the self-collection delivery costs optimization and estimation of future demand based on several socio-economic parameters.
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.
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.