A cyclic scheduling approach to maintaining production flow robustness

The organization of flow production, which is typical found in assembly processes, involves a repetitive, fixed-takt time flow of same-size production batches. The cyclic nature of the production flow, which ensures a steady production rhythm, enables just-in-time planning and organization of the associated supply chains. Disruptions in the operation of machinery and equipment, which occur in practice, lead to deviations from nominal operation times. These types of local disturbances lead to changes in production takt time, making it necessary to adjust previously created schedules for delivery/reception of materials and products. Assuming that a control action can be taken to adjust transport operation times within a specified time range, the problem of cyclic scheduling of production flows boils down to seeking conditions the satisfaction of which will guarantee robustness to this kind of disruptions. Satisfaction of robustness conditions allows a return to the nominal production takt time and appropriate adjustment of the production flow trajectory (which makes it possible for the system to return to the previously scheduled delivery times). Numerous examples are included to illustrate the principles of the proposed research methodology aimed at finding solutions for robust scheduling of fixed-takt time production flow. </jats:p

Towards a Reference Architecture for Context-Aware Services

This Chapter describes an infrastructure for multi-modal perceptual systems which aims at developing and realizing computer services that are delivered to humans in an implicit and unobtrusive way. The framework presented here supports the implementation of humancentric context-aware applications providing non-obtrusive assistance to participants in events such as meetings, lectures, conferences and presentations taking place in indoor "smart spaces". We emphasize on the design and implementation of an agent-based framework that supports "pluggable" service logic in the sense that the service developer can concentrate on the service logic independently of the underlying middleware. Furthermore, we give an example of the architecture’s ability to support the cooperation of multiple services in a meeting scenario using an intelligent connector service and a semantic web oriented travel service. The framework was developed as part of the project CHIL (Computers in the Human Interaction Loop). The vision of CHIL was to be able to provide context-aware human centric services which will operate in the background, provide assistance to the participants in the CHIL spaces and undertake tedious tasks in an unobtrusive way. To achieve this, significant effort had to be put in designing efficient context extraction components so that the CHIL system can acquire an accurate perspective of the current state of the CHIL space. However, the CHIL services required a much more sophisticated modelling of the actual event, rather than simple and fluctuating impressions of it. Furthermore, by nature the CHIL spaces are highly dynamic and heterogeneous; people join or leave, sensors fail or are restarted, user devices connect to the network, etc. To manage this diverse infrastructure, sophisticated techniques were necessary that can map all entities present in the CHIL system and provide information to all components which may require it. From these facts, one can easily understand that in addition to highly sophisticated components at an individual level, another mechanism (or a combination of mechanisms) should be present which can handle this infrastructure. The CHIL Reference Architecture for Multi Modal Systems lies in the background, and provides the solid, high performance and robust backbone for the CHIL services. Each individual need is assigned to a specially designed and integrated layer which is docked to the individual component, and provides all the necessary actions to enable the component to be plugged in the CHIL framework

A new open-source system for strategic freight logistics planning: the SYNCHRO-NET optimization tools

Globalization and e-commerce facilities have yielded in the recent years an incredibly huge increment of freight movements. Consequently, the underlying supply chains have become more and more complex to manage for the shipping companies, in terms of costs, distances, times, and environmental sustainability. SYNCHRO-NET, a H2020 European research project, aims to de-stress the international supply chains by fostering cost-effective and greener transportation alternatives. Besides other important actions, the SYNCHRO-NET framework provides an optimization and simulation toolset to support decision-making in freight logistics planning at a strategic level. The synchronized use of different transportation modes and the exploitation of smart steaming strategies for ship movements are the two main aspects considered in this innovative optimization system. In this paper, we present the optimization toolset developed, its contribution with respect to the existing platforms, and the experimental set-up implemented to evaluate its performance, usability, and effectiveness. The system is, in fact, currently under evaluation by several world-wide leading companies in freight logistics and transportation. However, the toolset potentialities go beyond the SYNCHRO-NET context, being the system an open-source project that makes use of open data formats and technologies

Doctor of Philosophy

dissertationData-driven analytics has been successfully utilized in many experience-oriented areas, such as education, business, and medicine. With the profusion of traffic-related data from Internet of Things and development of data mining techniques, data-driven analytics is becoming increasingly popular in the transportation industry. The objective of this research is to explore the application of data-driven analytics in transportation research to improve the traffic management and operations. Three problems in the respective areas of transportation planning, traffic operation, and maintenance management have been addressed in this research, including exploring the impact of dynamic ridesharing system in a multimodal network, quantifying non-recurrent congestion impact on freeway corridors, and developing infrastructure sampling method for efficient maintenance activities. First, the impact of dynamic ridesharing in a multimodal network is studied with agent-based modeling. The competing mechanism between dynamic ridesharing system and public transit is analyzed. The model simulates the interaction between travelers and the environment and emulates travelers' decision making process with the presence of competing modes. The model is applicable to networks with varying demographics. Second, a systematic approach is proposed to quantify Incident-Induced Delay on freeway corridors. There are two particular highlights in the study of non-recurrent congestion quantification: secondary incident identification and K-Nearest Neighbor pattern matching. The proposed methodology is easily transferable to any traffic operation system that has access to sensor data at a corridor level. Lastly, a high-dimensional clustering-based stratified sampling method is developed for infrastructure sampling. The stratification process consists of two components: current condition estimation and high-dimensional cluster analysis. High-dimensional cluster analysis employs Locality-Sensitive Hashing algorithm and spectral sampling. The proposed method is a potentially useful tool for agencies to effectively conduct infrastructure inspection and can be easily adopted for choosing samples containing multiple features. These three examples showcase the application of data-driven analytics in transportation research, which can potentially transform the traffic management mindset into a model of data-driven, sensing, and smart urban systems. The analytic

On designing heteroclinic networks from graphs

Copyright © 2013 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Physica D: Nonlinear Phenomena. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Physica D: Nonlinear Phenomena Vol. 265 (2013), DOI: 10.1016/j.physd.2013.09.006Robust heteroclinic networks are invariant sets that can appear as attractors in symmetrically coupled or otherwise constrained dynamical systems. These networks may have a very complicated structure that is poorly understood and determined to a large extent by the constraints and dimension of the system. As these networks are of great interest as dynamical models of biological and cognitive processes, it is useful to understand how particular graphs can be realised as robust heteroclinic networks that are attracting. This paper presents two methods of realizing arbitrarily complex directed graphs as robust heteroclinic networks for flows generated by ODEs---we say the ODEs {\em realise} the graphs as heteroclinic networks between equilibria that represent the vertices. Suppose we have a directed graph on $n_v$ vertices with $n_e$ edges. The "simplex realisation" embeds the graph as an invariant set of a flow on an $(n_v-1)$-simplex. This method realises the graph as long as it is one- and two-cycle free. The "cylinder realisation" embeds a graph as an invariant set of a flow on a $(n_e+1)$-dimensional space. This method realises the graph as long as it is one-cycle free. In both cases we find the graph as an invariant set within an attractor, and discuss some illustrative examples, including the influence of noise and parameters on the dynamics. In particular we show that the resulting heteroclinic network may or may not display "memory" of the vertices visited.Mathematical Biosciences Institute (MBI), OhioRoyal SocietyUniversity of Aucklan

Development of tour packages through spatio-temporal modelling of tourist movements

An ideal tour package should consist of itinerary elements such as the sequence of attractions with the scheduled arrival times and visiting durations at each attraction according to tourists’ preferences and characteristics. This research presents the methodology of designing tour packages by incorporating tourists’ spatio-temporal movements and tourist characteristics within scheduling processes. Therefore, it can provide tourists with personalised itineraries and support other stakeholders in managing the resources and facilities within attractions

CAMERA – Mobility Report 3

The EU-funded CAMERA (Coordination and Support Action for Mobility in Europe: Research and Assessment) project is coordinated by The Innaxis Foundation and Research Institute (Spain), in partnership with the University of Westminster (UK), Bauhaus Luftfahrt (Germany), EUROCONTROL (France-Belgium) and DeepBlue (Italy). It was launched in November 2017 for a duration of 48 months. The project investigates research initiatives into the European transport system from 2007, with a special focus on air travel, its integration with other transport modes, and passenger experience. Each year CAMERA assesses projects from different research programmes to deliver a European view of the state of aviation and mobility-related research activities. For this, the team relies on two main corner stones to its project approach: 1) the systematic development of a Performance Framework to provide a means of measuring; and 2) state-of-the-art algorithms for an automated analysis of the research projects

Passengers’ choices in multimodal public transport systems : A study of revealed behaviour and measurement methods

The concept of individual choice is a fundamental aspect when explaining and anticipating behavioural interactions with, and responses to, static and dynamic travel conditions in public transport (PT) systems. However, the empirical rounding of existing models used for forecasting travel demand, which itself is a result of a multitude of individual choices, is often insufficient in terms of detail and accuracy. This thesis explores three aspects, or themes, of PT trips – waiting times, general door-to-door path preferences, with a special emphasis on access and egress trip legs, and service reliability – in order to increase knowledge about how PT passengers interact with PT systems. Using detailed spatiotemporal empirical data from a dedicated survey app and PT fare card transactions, possible cross-sectional relationships between travel conditions and waiting times are analysed, where degrees of mental effort are gauged by an information acquisition proxy. Preferences for complete door-todoorpaths are examined by estimation of full path choice models. Finally, longitudinal effects of changing service reliability are analysed using a biennial panel data approach. The constituent studies conclude that there are otherexplanatory factors than headway that explain waiting times on first boarding stops of PT trips and that possession of knowledge of exact departure times reduces mean waiting times. However, this information factor is not evidentin full path choice, where time and effort-related preferences dominate with a consistent individual preference factor. Finally, a statistically significant on-average adaption to changing service reliability is individual-specific andnon-symmetrical depending on the direction of reliability change, where a relatively large portion of the affected individuals do not appear to respond to small-scale perturbations of reliability while others do, all other thingsbeing equal

Promoting Intermodal Connectivity at California’s High Speed Rail Stations

High-speed rail (HSR) has emerged as one of the most revolutionary and transformative transportation technologies, having a profound impact on urban-regional accessibility and inter-city travel across Europe, Japan, and more recently China and other Asian countries. One of HSR’s biggest advantages over air travel is that it offers passengers a one-seat ride into the center of major cities, eliminating time-consuming airport transfers and wait times, and providing ample opportunities for intermodal transfers at these locales. Thus, HSR passengers are typically able to arrive at stations that are only a short walk away from central business districts and major tourist attractions, without experiencing any of the stress that car drivers often experience in negotiating such highly congested environments. Such an approach requires a high level of coordination and planning of the infrastructural and spatial aspects of the HSR service, and a high degree of intermodal connectivity. But what key elements can help the US high-speed rail system blend successfully with other existing rail and transit services? That question is critically important now that high-speed rail is under construction in California. The study seeks to understand the requirements for high levels of connectivity and spatial and operational integration of HSR stations and offer recommendations for seamless, and convenient integrated service in California intercity rail/HSR stations. The study draws data from a review of the literature on the connectivity, intermodality, and spatial and operational integration of transit systems; a survey of 26 high-speed rail experts from six different European countries; and an in-depth look of the German and Spanish HSR systems and some of their stations, which are deemed as exemplary models of station connectivity. The study offers recommendations on how to enhance both the spatial and the operational connectivity of high-speed rail systems giving emphasis on four spatial zones: the station, the station neighborhood, the municipality at large, and the region