Assigning gates to flights considering physical, operational, and temporal constraints is known as the Gate Assignment Problem. This article proposes the novelty of coupling a commercial stand and gate allocation software with an off-the-grid optimization algorithm. The software provides the assignment costs, verifies constraints and restrictions of an airport, and provides an initial allocation solution. The gate assignment problem was solved using a genetic algorithm. To improve the robustness of the allocation results, delays and early arrivals are predicted using a random forest regressor, a machine learning technique and in turn they are considered by the optimization algorithm. Weather data and schedules were obtained from Zurich International Airport. Results showed that the combination of the techniques result in more efficient and robust solutions with higher degree of applicability than the one possible with the sole use of them independently.
Airport management is regularly challenged by the task of assigning flights to existing parking positions in the most efficient way while complying with existing policies, restrictions and capacity limitations. However, such process is frequently disrupted by various events, affecting punctuality of airline operations. This paper describes an innovative approach for obtaining an efficient stand assignment considering the stochastic nature of airport environment. Furthermore, the presented methodology combines benefits of Bayesian modelling and metaheuristics for generating solutions that are more robust to airport flight schedule perturbations. In addition, this paper illustrates that the application of the presented methodology combined with simulation provides a valuable tool for assessing the robustness of the developed stand assignment to flight delays.
A transition of today’s energy system towards renewableresources, requires solutions to match renewable energy generationwith demand over time. These solutions include smartgrids, demand-side management and energy storage. Energycan be stored during moments of overproduction of renewableenergy and used from the storage during moments ofinsufficient production. Allocation in real time of generatedenergy towards controlled appliances or storage chargers, isdone by a smart control system which makes decisions basedon predictions (of upcoming generation and demand) andinformation of the actual condition of storages.
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DISCO aims at fast-tracking upscaling to new generation of urban logistics and smart planning unblocking the transition to decarbonised and digital cities, delivering innovative frameworks and tools, Physical Internet (PI) inspired. To this scope, DISCO will deploy and demonstrate innovative and inclusive urban logistics and planning solutions for dynamic space re-allocation integrating urban freight at local level, within efficiently operated network-of-networks (PI) where the nodes and infrastructure are fixed and mobile based on throughput demands. Solutions are co-designed with the urban logistics community – e.g., cities, logistics service providers, retailers, real estate/public and private infrastructure owners, fleet owners, transport operators, research community, civil society - all together moving a paradigm change from sprawl to data driven, zero-emission and nearby-delivery-based models.
For English see below In dit project werkt het Lectoraat ICT-innovaties in de Zorg van hogeschool Windesheim samen met zorganisaties de ZorgZaak, De Stouwe, en IJsselheem en daarnaast Zorgcampus Noorderboog, Zorgtrainingscentrum Regio Zwolle, Patiëntenfederatie NPCF, VitaalThuis, ActiZ, Vilans, V&VN, Universiteit Twente en het Lectoraat Innoveren in de Ouderenzorg van Windesheim aan het in staat stellen van wijkverpleegkundigen om autonoom en doelmatig, op basis van klinisch redeneren, eHealth te indiceren en in te zetten bij cliënten. De aanleiding voor dit project wordt gevormd door de wijzigingen per 1 januari 2015 in de Zorgverzekeringswet. Wijkverpleegkundigen zijn sindsdien zelf verantwoordelijk voor de indicatiestelling en zorgtoewijzing voor verzorging en verpleging thuis: zij moeten bepalen welke zorg hun cliënten nodig hebben gezien hun individuele situaties, en hoe die zorg het best geleverd kan worden. Zorgverzekeraars leggen hierbij minimumeisen op, o.a. met betrekking tot de inzet van eHealth. Wijkverpleegkundigen hebben op dit moment echter niet of nauwelijks ervaring met het inzetten en toepassen van technologische toepassingen zoals eHealth. Vraagarticulatie leidde tot de volgende praktijkvraagstelling: 1. Hoe kunnen wijkverpleegkundigen worden voorzien in hun informatiebehoefte over eHealth? 2. Hoe kunnen wijkverpleegkundigen worden ondersteund in hun klinisch redeneren over het inzetten van eHealth bij hun cliënten? 3. Hoe kunnen wijkverpleegkundigen worden ondersteund bij het inzetten van eHealth in hun zorgproces? Het project levert hiertoe drie bijdragen: - De eerste bijdrage is een duurzaam geborgde keuzehulp (een app voor tablet of smartphone) waarmee wijkverpleegkundigen toegang hebben tot de benodigde informatie over eHealth-toepassingen en die aansluit bij de manier waarop wijkverpleegkundigen zorg indiceren (bijvoorbeeld door relaties te leggen tussen NIC-interventies en bijpassende eHealth-toepassingen). - Informatievoorziening is niet een afdoende antwoord op de handelingsverlegenheid van de wijkverpleegkundige omdat eHealth sterk in ontwikkeling is en blijft waardoor er altijd een discrepantie zal bestaan tussen de beschikbare en de benodigde informatie. . De tweede bijdrage van dit project is daarom kennis over (en inzicht in) het klinisch redeneren over de inzet van eHealth. Deze kennis wordt in het project doorvertaald naar een trainingsmodule die erop is gericht om het klinisch redeneren van wijkverpleegkundigen over het inzetten van eHealth en andere thuiszorgtechnologie bij hun cliënten te versterken. - De derde bijdrage van dit project omhelst inbedding van bovengenoemde resultaten in het verpleegkunde-onderwijs van onder meer Windesheim en in nascholingstrajecten voor wijkverpleegkundigen. Voor duurzame, bredere inbedding in het onderwijs wordt samengewerkt met regionale zorgonderwijsnetwerken. In this project the research group IT-innovations in Health Care of Windesheim University of Applied Sciences cooperates with care organisations de ZorgZaak, De Stouwe, and IJsselheem, and stakeholders Zorgcampus Noorderboog, Zorgtrainingscentrum Regio Zwolle, Patiëntenfederatie NPCF, VitaalThuis, ActiZ, Vilans, V&VN, University of Twente, and research group Innovation of Care of Older Adults of Windesheim to enable home care nurses to autonomously and adequately, based on clinical reasoning, allocate eHealth and implement it in patient care. The motivation behind this project lies in the alterations in the care insurance legislation per January 2015. Since then, home care nurses are responsible for the care allocation of all care at home: they determine which care their clients require, taking into account the individual situations, and how this care can best be delivered. Care insurance companies impose minimum requirements for this allocation of home care, among others concerning the implementation of eHealth. Home care nurses, however, have no or limited information about and experience with technical applications like eHealth. Articulation of the demands of home care nurses resulted in the following questions: 1. How can home care nurses be provided with information concerning eHealth? 2. How can home care nurses be supported in their clinical reasoning about the deployment of eHealth by their patients? 3. How can home care nurses be supported when deploying eHealth in their care process? This project contributes in three ways: " The first contribution is a sustainable selection tool (an app for tablet or smartphone) to be used by home care nurses to provide them with the required information about eHealth applications. This selection tool will work in accordance with how home care nurses allocate care, e.g. by relating NIC-interventions to matching eHealth applications. " Providing information is an insufficient, although necessary, answer to the demands of home care nurses because of continuously developing eHealth applications. Hence, the second contribution of this project is knowledge about (and insight in) the clinical reasoning about the deployment of eHealth. This knowledge will be converted into a training module aimed at strengthening the clinical reasoning about the deployment of eHealth by their patients. " The third contribution of this project concerns embedding the selection tool and the training module in regular education (among others at Windesheim) and in refresher courses for home care nurses. Cooperation with regional care education networks will ensure sustainable and broad embedding of both the selection tool and the training module.
In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
