Dimensions of data sparseness and their effect on supply chain visibility

Supply chain visibility concerns the ability to track parts, components, or products in transit from supplier to customer. The data that organizations can obtain to establish or improve supply chain visibility is often sparse. This paper presents a classification of the dimensions of data sparseness and quantitatively explores the impact of...

Incorporating Trust into Context-Aware Services

Enabling technologies concerning hardware, networking, and sensing have inspired the development of context-aware IT services. These adapt to the situation of the user, such that service provisioning is specific to his/her corresponding needs. We have seen successful applications of context-aware services in healthcare, well-being, and smart...

Particle filter–based data assimilation in dynamic data-driven simulation: sensitivity analysis of three critical experimental conditions

Data assimilation (DA) is a methodology widely used by different disciplines of science and engineering. It is typically applied to continuous systems with numerical models. The application of DA to discrete-event and discrete-time systems including agent-based models is relatively new. Because of its non-linearity and non-Gaussianity, the...

Combining Context-Awareness and Data Analytics in Support of Drone Technology

Drones performing an autonomous mission need to adapt to frequent changes in their environment. In other words, they have to be context-aware. Most current context-aware systems are designed to distinguish between situations that have been pre-defined in terms of anticipated situation types and corresponding desired behavior types. This only...

Strategic Use of Data Assimilation for Dynamic Data-Driven Simulation

Dynamic data-driven simulation (DDDS) incorporates real-time measurement data to improve simulation models during model run-time. Data assimilation (DA) methods aim to best approximate model states with imperfect measurements, where particle Filters (PFs) are commonly used with discrete-event simulations. In this paper, we study three critical...

Concepts and Constructs of Urban Sensing

There is an increasing practice of combining various sorts of data from the city to obtain a comprehensive operating picture for urban managers. The sorts of data being combined includes administrative data, sensor and transactional data, and social media data. In order for these practices to fulfil their full promises it is important that...

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from...

A particle filter-based data assimilation framework for discrete event simulations

With the advent of new sensor technologies and communication solutions, the availability of data for discrete event systems has greatly increased. This motivates research on data assimilation for discrete event simulations that has not yet fully matured. This paper presents a particle filter-based data assimilation framework for discrete event...

Exploring challenges and solutions for container transportation using rail: A modelling and simulation gaming study

Rail is a cost-effective and environment friendly freight transport modality when used efficiently. Stakeholders around Dutch ports are discouraged to choose rail due to uncertain train schedules and the dispersed nature of freight flows across terminals in the port. To understand the challenges and opportunities of freight transport using rail,...

Data Assimilation in Discrete Event Simulations: A Rollback Based Sequential Monte Carlo Approach

Data assimilation is an analysis technique which aims to incorporate measured observations into a dynamic system model in order to produce accurate estimates of the current state variables of the system. Although data assimilation is conventionally applied in continuous system models, it is also a desired ability for its discrete event...

Exploring strategies in integrated container terminal planning tasks: A data-intensive simulation game analysis

Planning tasks in modern, fully automated container terminals require a high awareness of the complex situation, and successful planning strategies. Operational planning includes both strategies of planning and resource management. As planning procedures are not (yet) fully automated, a skilled workforce of planners is needed to conduct the...