Ports are actively pursuing greater operational efficiency to effectively handle the increasing global flow of goods, while striving to improve the energy efficiency of their operations to comply with new environmental regulations. As a result, innovation-leading ports have begun to recognize the potential of digital twins to overview, coordinate and optimize port processes, resulting in energy savings, and reductions of costs and of CO2 emissions. While digital twins have gained momentum in other domains such as smart manufacturing and aerospace, their adoption in ports has been comparatively slow. This can be explained, among other things, by the multi-stakeholder nature of the port and the high complexity of the often interconnected port processes. Thus, this thesis, grounded in the context of ports, discusses what constitutes a digital twin, proposes characteristics to assess the maturity of existing digital twins, and introduces and evaluates mathematical models to support a key port process, which can be used as components of a digital twin for the port. The thesis is composed of three papers:  Paper 1 is based on an extensive literature review, through which digital twins among different domains are studied in depth in order to transfer insights from these to the port domain. The resulting discussion of what constitutes a port’s digital twin and the requirements that a port’s digital twin must fulfil, together with a discussion of use cases of how port digital twins can contribute to energy savings, form the basis of Paper 1.  Paper 2 discusses how digital twins’ maturity can be assessed within six maturity levels and presents milestones for their implementation. Notably, Interoperability is identified as the highest maturity level, as the numerous stakeholders and their respective digital twins must work together to reach a coordinated system of systems performance. Using this assessment demonstrates that only a few innovation-leading ports have developed sophisticated digital twinning solutions so far.  Paper 3 is dedicated to coordinating container retrieval with stacking, combining two key port operations. Thus, it can present a key modeling component of a port digital twin, considering jointly the goals of reducing the energy demanding crane movements, as well as keeping schedules tight to avoid port congestion issues. This is directly reflecting the potentially conflicting perspectives of different stakeholders in the port context. The provided optimization model and algorithm show that jointly addressing both problems may lead to a reduced efficiency of both individual objectives, but from a systems perspective, leads to a higher overall port efficiency. / Hamnar strävar aktivt efter ökad operativ effektivitet för att hantera den ökande globala varuflödet, samtidigt som de strävar efter att förbättra energieffektiviteten. Som ett resultat har ledande hamnar börjat se potentialen hos digitala tvillingar för att skapa överblick samt koordinera och optimera processer i hamnen. Målet med användningen av digitala tvillingar är energibesparingar samt minskning av kostnader och CO2-utsläpp. Medan digitala tvillingar har använts inom andra områden såsom tillverknings-, flyg- och rymdindustrin, har införandet i hamnar varit jämförelsevist långsamt. Detta kan förklaras, bland annat, av hamnens många olika involverade aktörer och den höga komplexiteten i de ofta sammanlänkade hamnprocesserna. Därför fokuserar denna avhandling, med utgångspunkt i hamnkontexten, vad som utgör en digital tvilling, presenterar egenskaper för olika mognadsnivåer hos befintliga digitala tvillingar, och introducerar samt utvärderar matematiska modeller som kan bli delkomponenter i en digital tvilling för hamnen. Avhandlingen består av tre artiklar: Artikel 1 bygger på en omfattande litteraturöversikt, inom vilken digitala tvillingar för olika områden studeras ingående för att överföra insikter från dessa till hamndomänen. Detta resulterar i en presentation av vad som utgör en hamns digitala tvilling och de krav som en hamns digitala tvilling måste uppfylla, tillsammans med en diskussion om möjliga sett på vilka hur hamnens digitala tvillingar kan bidra till energibesparingar. Artikel 2 presenterar ett ramverk för hur mognaden hos digitala tvillingar kan bedömas baserat på sex mognadsnivåer och presenterar milstolpar för deras implementering. Noterbart är att interoperabilitet identifieras som den högsta mognadsnivån, eftersom de många intressenterna och deras respektive digitala tvillingar måste koordineras för att nå en fungerande system-av-systemnviå. Genom att använda denna bedömning visar det sig att endast några få innovationsledande hamnar hittills har utvecklat sofistikerade digitala tvillinglösningar. Artikel 3 fokuserar på koordinering av containerupphämtning koordinerat med staplings effektivitet, två viktiga hamnaktivieter. Därför representerar dessa en viktig modelleringskomponent i en hamns digitala tvilling, med beaktande av målen att minska de energikrävande kranrörelse, samt behovet av att hålla planerade tider för att undvika trängsel och väntan. Detta speglar direkt de potentiellt konfliktfyllda perspektiven hos olika intressenter i hamnkontexten. Den utvecklade optimeringsmodellen och algoritmen visar att gemensam hantering av båda dessa problemen kan leda till en minskad effektivitet för de respektive individuella målen, men en ökad effektivitet från ett systemperspektiv för hamnen som helhet.

No description available.

Ports are actively pursuing greater operational efficiency to effectively handle the increasing global flow of goods, while striving to improve the energy efficiency of their operations to comply with new environmental regulations. As a result, innovation-leading ports have begun to recognize the potential of digital twins to overview, coordinate and optimize port processes, resulting in energy savings, and reductions of costs and of CO2 emissions. While digital twins have gained momentum in other domains such as smart manufacturing and aerospace, their adoption in ports has been comparatively slow. This can be explained, among other things, by the multi-stakeholder nature of the port and the high complexity of the often interconnected port processes. Thus, this thesis, grounded in the context of ports, discusses what constitutes a digital twin, proposes characteristics to assess the maturity of existing digital twins, and introduces and evaluates mathematical models to support a key port process, which can be used as components of a digital twin for the port. / Hamnar strävar aktivt efter ökad operativ effektivitet för att hantera den ökande globala varuflödet, samtidigt som de strävar efter att förbättra energieffektiviteten. Som ett resultat har ledande hamnar börjat se potentialen hos digitala tvillingar för att skapa överblick samt koordinera och optimera processer i hamnen. Målet med användningen av digitala tvillingar är energibesparingar samt minskning av kostnader och CO2-utsläpp. Medan digitala tvillingar har använts inom andra områden såsom tillverknings-, flyg- och rymdindustrin, har införandet i hamnar varit jämförelsevist långsamt. Detta kan förklaras, bland annat, av hamnens många olika involverade aktörer och den höga komplexiteten i de ofta sammanlänkade hamnprocesserna. Därför fokuserar denna avhandling, med utgångspunkt i hamnkontexten, vad som utgör en digital tvilling, presenterar egenskaper för olika mognadsnivåer hos befintliga digitala tvillingar, och introducerar samt utvärderar matematiska modeller som kan bli delkomponenter i en digital tvilling för hamnen.

Les décisions collaboratives sous incertitude dans les situations non urgentes peuvent être retardées, surtout lorsque la santé humaine et des investissements élevés sont en jeu comme c’est le cas des projets de R and D pharmaceutiques. Cette thèse étudie les causes des retards récurrents dans la prise de décision collaborative sous incertitude et les pratiques efficientes pour réduire ces retards. Pour mieux comprendre le problème des retards dans la prise de décision face à l’incertitude, nous étudions d’abord la notion d’incertitude et proposons une définition de l’incertitude adaptée au management de projet. Ensuite, le processus de prise de décision dans les projets de développement de nouveaux médicaments est modélisé, mettant en évidence le cycle de vie de l’information à partir de sa production jusqu’à sa consommation c’est-à-dire la décision elle-même. Ce modèle comprend une étape de réflexion individuelle et une étape de l’interaction en groupe, en clarifiant comment l’information est traitée différemment par les décideurs. Afin d’analyser les conflits du passé et anticiper ceux du futur, sur la base de ce modèle, un indice est défini pour mesurer le risque d’invalidation d’une décision prise a posteriori. Finalement, à travers des entretiens approfondis, 252 facteurs clés qui influent la prise de décision sont identifiés. Les trois causes de retard les plus citées sont : la peur de l’incertitude, la peur de la hiérarchie et la difficulté des décisions d’arrêt. Sur la base des facteurs identifiés, un recueil de bonnes pratiques est construit pour les acteurs du processus de prise de décision qui aident à former, mûrir, communiquer, digérer, respecter et finalement exécuter les décisions collaboratives. / Collaborative decisions may be deferred when faced with a high degree of uncertainty, especially when public health and high investments are at stake and in situations that seem non-urgent, as is the case in pharmaceutical R and D projects. This thesis investigates the causes of recurrent delay in collaborative decision-making under uncertainty, and the efficient practices to reduce this delay. To better understand the problem of delay in decision-making under uncertainty, we first review the notion of uncertainty and propose a definition of uncertainty adapted to project management. Then, the decision-making process in drug development projects is modeled, highlighting the information life cycle from its generation to its consumption i.e. the decision itself. It includes individual reflection and group interaction, clarifying how information is processed differently by decision-makers. To analyze past conflicts and anticipate future ones, based on this model, an index is defined that measures the risk of invalidating a decision a posteriori. Finally, through an in-depth interview-based approach, 252 key factors that affect decision-making are pointed out. The three most-mentioned causes of delay are: fear of uncertainty, fear of hierarchy, and difficulty of No Go decisions. Based on the identified factors, a compendium of practices is constructed for the actors of the decision-making process that help collaborative decisions to be formed, matured, digested, respected, and finally executed.

This thesis is focused on airport departure operations; its objective is to assign a value to surface surveillance information within a collaborative framework. The research develops a cooperative concept that improves the control of departure operations at busy airports and evaluates its merit using a classical and widely accepted airport departure model. The research then assumes departure operations are collaboratively controlled and develops a stochastic model of taxi operations on the airport surface. Finally, this study investigates the effect of feeding back different levels of surface surveillance information to the departure control process. More specifically, it examines the environmental and operational impact of aircraft surface location information on the taxi clearance process. Benefits are evaluated by measuring and comparing engine emissions for given runway utilization rates.

Ce manuscrit expose notre travail dans le cadre du projet IWARD et détaille la couche de gestion et de décision du groupement de robots. Ce projet avait comme objectif d’assister le personnel médical dans leur travail, ceci est réalisé en utilisant des robots mobiles, reconfigurables, et rechargeables. Ces robots sont conçus pour effectuer des taches logistiques comme : Le transport de médicaments, le nettoyage, le guidage des patients, la surveillance et la téléconsultation. Dans la première partie de la thèse nous présenterons le problème stratégique qui consiste à déterminer les plannings de rechargement des robots, la configuration des robots opérationnels ainsi que la localisation des stations d’attentes des robots lorsqu’ils sont en état de veille. Différentes hiérarchies à plusieurs niveaux de décisions, sont formulées comme des programmes linéaires en nombres entiers. Des formulations utilisant l’approche de génération de colonnes sont aussi développées pour résoudre ces problèmes. Dans la deuxième partie, le problème tactique est exposé, ceci consiste à affecter les taches arrivantes aux différents robots et d’ordonnancer dynamiquement l’exécution ces missions. Deux approches sont inspectées une version centralisée utilisant les algorithmes évolutionnaires et une autre version distribuée utilisant les algorithmes d’enchères inversées. Afin de mettre à l épreuve ces deux approches, une simulation a événements discrets a été conçue et développée spécifiquement pour le projet, permettant ainsi d’évaluer ces deux approches. / Due to the expansion of the life duration and the shortage of medical personal in hospitals the EU funded IWARD project as part of the IFP6 program. The aims of this project were to assist the medical personnel in logistic and non medical tasks (transport, cleaning, environmental monitoring, guidance and tele-monitoring) through the usage of mobile, reconfigurable, rechargeable robots, thus letting the Medical staff to concentrate on medical aspects of their work.This thesis was part of this project, and our work consisted on developing a decision making framework for the team of robots.In the first part of the thesis, we address the strategic decisions essentially the: (i) the robots’ home station location problem, (ii) Robot‘s reconfiguration problems and (iii) Robots recharging scheduling. We formulate those problems as a linear problems and we propose to solve them using Mixed Integer Programming (MIP). We also present a formulation using a column generation approach to solve those problems.In the later part we address the tactical problems, mainly the mission assignment, the mission scheduling and rescheduling. We present two different approaches; a centralized decision finder implemented using genetic algorithms. And a decentralized approach using auction like and market based algorithms in order to provided collaborative decision making framework.Finally we compare those two approaches using a custom made discrete event simulation (DES).

In recent years, the development considerations within transport planning have started to examine needs from a more comprehensive perspective in order to shift the focus of planning away from favoring automobile travel. New approaches are emerging around the world to face the challenges we are confronted with, such as urbanization, dispersion of community structures, change in population structure, aging, climate change, and tightening budgets. Therefore, this thesis is aiming to gain more insight on new approaches in transport planning by comparing emerging systems in Sweden and in Finland. The comparison is focused on the renewed procedures at the early stages of transport planning; the methods to conduct multi-modal studies through collaborative decision-making processes in both countries. Thus, in this thesis the renewed preliminary transport planning in Finland and the Swedish method of Strategic Choice of Measures are compared based on implications from practice. The main purpose is to learn from practice and therefore, the data for comparison is based on conducted test cases that aim to develop the emerging planning processes in both countries. In Sweden, the preliminary version of the new planning method, developed by the Swedish Transport Administration, was tested with six cases during 2011. KTH was commissioned to conduct a study to examine the collaborative planning of involved actors in each of these cases, and the cases together. Thus, in the Swedish context, the data for comparison will be collected from the earlier study conducted by a KTH researcher John Odhage. In the Finnish context, a case study will be carried out for the data collection. The chosen case consists of a pilot study initiated in Finland in 2012 for the purpose of collecting ideas for the development of a renewed preliminary planning process. In general, both countries approaches aim at creating efficient procedures that would contribute to cost-efficiency and sustainable development as well as fulfilling other aims of the transport policy of each country.  The focus of the comparison is on the critical aspects of multi-modal studies and three features of a collaborative process; the choice of actors, the problem formulation, and the process management. The comparison is carried out based on theoretical implications and the experiences from practice are scrutinized against the ideal approach of each country. It has become apparent that three clearly distinctive differences between the approaches can be pointed out: the role of the transport administration, the creation of a steering committee, and creation of a concept for process guidance. In addition, the four-step principle is the multi-modal tool used in both countries approaches to generate alternative measures to transport related issues. The basic idea of the principle is in the first place to influence land use, transport demand, and choice of travel mode, and secondly to examine if the use of existing transport system can be optimized prior to construction. However, based on the experiences from practice, it seems that in both countries processes the focus of generating alternative measures is leaning more against minor or large new investments. Thus, the search for complementary measures to achieve considerable cost-savings and more importantly, sustainable development, is perceived challenging.

Worsening climate change impacts, particularly in coastal areas, are forcing urban planners and designers to find new approaches to govern cities. Traditional government approaches are failing to equip cities with effective strategies on how to implement sustainable interventions such as green and blue infrastructure. Adaptive governance has emerged as a way of dealing with the inherent uncertainty and unpredictability of complex social-ecological systems. It is neither top-down nor bottom-up but involves innovative ways of solving problems with emphasis on collaborative decision-making. This research focuses specifically on how collaboration is undertaken in adaptive governance processes by examining The Soul of Nørrebro case study—an integrated urban design and climate adaptation project for Hans Tavsens Park and Korsgade in Copenhagen, Denmark. Through desk study and interviews, the study identifies which stakeholders are involved in collaborative decision-making processes and how stakeholders envision, implement, and contest collaborative decision-making in The Soul of Nørrebro green and blue infrastructure project. This research found that participation from a wide range of local stakeholders and citizens is an integral part of redesigning public space, as it helps create cohesive, just, and ecologically productive environments. However, trade-offs that result in political decisions that are desirable to some and not to others cannot be avoided in the end. While certain setbacks were unavoidable, others that were encountered could have perhaps been prevented through increased transdisciplinary and representative collaboration.

No description available.

We develop and evaluate two significant modeling concepts within the context of a large-scale Airspace Planning and Collaborative Decision-Making Model (APCDM) and, thereby, enhance its current functionality in support of both strategic and tactical level flight assessments. The first major concept is a new severe weather-modeling paradigm that can be used to assess existing tactical en route flight plan strategies such as the Flight Management System (FMS) as well as to provide rerouting strategies. The second major concept concerns modeling the mediated bartering of slot exchanges involving airline trade offers for arrival/departure slots at an arrival airport that is affected by the Ground Delay Program (GDP), while simultaneously considering issues related to sector workloads, airspace conflicts, as well as overall equity concerns among the airlines. This research effort is part of an $11.5B, 10-year, Federal Aviation Administration (FAA)-sponsored program to increase the U.S. National Airspace (NAS) capacity by 30 percent by the year 2010. Our innovative contributions of this research with respect to the severe weather rerouting include (a) the concept of "Probability-Nets" and the development of discretized representations of various weather phenomena that affect aviation operations; (b) the integration of readily accessible severe weather probabilities from existing weather forecast data provided by the National Weather Service (NWS); (c) the generation of flight plans that circumvent severe weather phenomena with specified probability levels, and (d) a probabilistic delay assessment methodology for evaluating planned flight routes that might encounter potentially disruptive weather along its trajectory. Given a fixed set of reporting stations from the CONUS Model Output Statistics (MOS), we begin by constructing weather-specific probability-nets that are dynamic with respect to time and space. Essential to the construction of the probability-nets are the point-by-point forecast probabilities associated with MOS reporting sites throughout the United States. Connections between the MOS reporting sites form the strands within the probability-nets, and are constructed based upon a user-defined adjacency threshold, which is defined as the maximum allowable great circle distance between any such pair of sites. When a flight plan traverses through a probability-net, we extract probability data corresponding to the points where the flight plan and the probability-net strand(s) intersect. The ability to quickly extract this trajectory-related probability data is critical to our weather-based rerouting concepts and the derived expected delay and related cost computations in support of the decision-making process. Next, we consider the superimposition of a flight-trajectory-grid network upon the probability-nets. Using the U.S. Navigational Aids (Navaids) as the network nodes, we develop an approach to generate flight plans that can circumvent severe weather phenomena with specified probability levels based on determining restricted, time-dependent shortest paths between the origin and destination airports. By generating alternative flight plans pertaining to specified threshold strand probabilities, we prescribe a methodology for computing appropriate expected weather delays and related disruption factors for inclusion within the APCDM model. We conclude our severe weather-modeling research by conducting an economic benefit analysis using a k-means clustering mechanism in concert with our delay assessment methodology in order to evaluate delay costs and system disruptions associated with variations in probability-net refinement-based information. As a flight passes through the probability-net(s), we can generate a probability-footprint that acts as a record of the strand intersections and the associated probabilities from origin to destination. A flight plan's probability-footprint will differ for each level of data refinement, from whence we construct route-dependent scenarios and, subsequently, compute expected weather delay costs for each scenario for comparative purposes. Our second major contribution is the development of a novel slot-exchange modeling concept within the APCDM model that incorporates various practical issues pertaining to the Ground Delay Program (GDP), a principal feature in the FAA's adoption of the Collaborative Decision-Making (CDM) paradigm. The key ideas introduced here include innovative model formulations and several new equity concepts that examine the impact of "at-least, at-most" trade offers on the entire mix of resulting flight plans from respective origins to destinations, while focusing on achieving defined measures of "fairness" with respect to the selected slot exchanges. The idea is to permit airlines to barter assigned slots at airports affected by the Ground Delay Program to their mutual advantage, with the FAA acting as a mediator, while being cognizant of the overall effect of the resulting mix of flight plans on air traffic control sector workloads, collision risk and safety, and equity considerations. We start by developing two separate slot-exchange approaches. The first consists of an external approach in which we formulate a model for generating a set of package-deals, where each package-deal represents a potential slot-exchange solution. These package-deals are then embedded within the APCDM model. We further tighten the model representation using maximal clique cover-based cuts that relate to the joint compatibility among the individual package-deals. The second approach significantly improves the overall model efficiency by automatically generating package-deals as required within the APCDM model itself. The model output prescribes a set of equitable flight plans based on admissible trades and exchanges of assigned slots, which are in addition conformant with sector workload capabilities and conflict risk restrictions. The net reduction in passenger-minutes of delay for each airline is the primary metric used to assess and compare model solutions. Appropriate constraints are included in the model to ensure that the generated slot exchanges induce nonnegative values of this realized net reduction for each airline. In keeping with the spirit of the FAA's CDM initiative, we next propose four alternative equity methods that are predicated on different specified performance ratios and related efficiency functions. These four methods respectively address equity with respect to slot-exchange-related measures such as total average delay, net delay savings, proportion of acceptable moves, and suitable value function realizations. For our computational experiments, we constructed several scenarios using real data obtained from the FAA based on the Enhanced Traffic Management System (ETMS) flight information pertaining to the Miami and Jacksonville Air Route Traffic Control Centers (ARTCC). Through our experimentation, we provide insights into the effect of the different proposed modeling concepts and study the sensitivity with respect to certain key parameters. In particular, we compare the alternative proposed equity formulations by evaluating their corresponding slot-exchange solutions with respect to the net reduction in passenger-minutes of delay for each airline. Additionally, we evaluate and compare the computational-effort performance, under both time limits and optimality thresholds, for each equity method in order to assess the efficiency of the model. The four slot-exchange-based equity formulations, in conjunction with the internal slot-exchange mechanisms, demonstrate significant net savings in computational effort ranging from 25% to 86% over the original APCDM model equity formulation. The model has been implemented using Microsoft Visual C++ and evaluated using a C++ interface with CPLEX 9.0. The overall results indicate that the proposed modeling concepts offer viable tools that can be used by the FAA in a timely fashion for both tactical purposes, as well as for exploring various strategic issues such as air traffic control policy evaluations; dynamic airspace resectorization strategies as a function of severe weather probabilities; and flight plan generation in response to various disruption scenarios. / Ph. D.