Industrial and Tramp Ship Routing Problems: Closing the Gap for Real-Scale Instances

Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristics pose considerable challenges for exact and heuristic methods, and some cases with as few as 18 cargoes remain unsolved. To face this challenge, we propose an exact branch-and-price (B&P) algorithm and a hybrid metaheuristic. Our exact method generates elementary routes, but exploits decremental state-space relaxation to speed up column generation, heuristic strong branching, as well as advanced preprocessing and route enumeration techniques. Our metaheuristic is a sophisticated extension of the unified hybrid genetic search. It exploits a set-partitioning phase and uses problem-tailored variation operators to efficiently handle all the problem characteristics. As shown in our experimental analyses, the B&P optimally solves 239/240 existing instances within one hour. Scalability experiments on even larger problems demonstrate that it can optimally solve problems with around 60 ships and 200 cargoes (i.e., 400 pickup and delivery services) and find optimality gaps below 1.04% on the largest cases with up to 260 cargoes. The hybrid metaheuristic outperforms all previous heuristics and produces near-optimal solutions within minutes. These results are noteworthy, since these instances are comparable in size with the largest problems routinely solved by shipping companies

Cloud Workload Allocation Approaches for Quality of Service Guarantee and Cybersecurity Risk Management

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies. Allowing several services or Virtual Machines (VMs) to commonly share the cloud\u27s infrastructure enables cloud providers to optimize resource usage, power consumption, and operating expense. However, servers sharing among users and VMs causes performance degradation and results in cybersecurity risks. Consequently, how to develop efficient and effective resource management policies to make the appropriate decisions to optimize the trade-offs among resource usage, service quality, and cybersecurity loss plays a vital role in the sustainable future of cloud computing. In this dissertation, we focus on cloud workload allocation problems for resource optimization subject to Quality of Service (QoS) guarantee and cybersecurity risk constraints. To facilitate our research, we first develop a cloud computing prototype that we utilize to empirically validate the performance of different proposed cloud resource management schemes under a close to practical, but also isolated and well-controlled, environment. We then focus our research on the resource management policies for real-time cloud services with QoS guarantee. Based on queuing model with reneging, we establish and formally prove a series of fundamental principles, between service timing characteristics and their resource demands, and based on which we develop several novel resource management algorithms that statically guarantee the QoS requirements for cloud users. We then study the problem of mitigating cybersecurity risk and loss in cloud data centers via cloud resource management. We employ game theory to model the VM-to-VM interdependent cybersecurity risks in cloud clusters. We then conduct a thorough analysis based on our game-theory-based model and develop several algorithms for cybersecurity risk management. Specifically, we start our cybersecurity research from a simple case with only two types of VMs and next extend it to a more general case with an arbitrary number of VM types. Our intensive numerical and experimental results show that our proposed algorithms can significantly outperform the existing methodologies for large-scale cloud data centers in terms of resource usage, cybersecurity loss, and computational effectiveness

Towards the reduction of greenhouse gas emissions : models and algorithms for ridesharing and carbon capture and storage

Avec la ratification de l'Accord de Paris, les pays se sont engagés à limiter le réchauffement climatique bien en dessous de 2, de préférence à 1,5 degrés Celsius, par rapport aux niveaux préindustriels. À cette fin, les émissions anthropiques de gaz à effet de serre (GES, tels que CO2) doivent être réduites pour atteindre des émissions nettes de carbone nulles d'ici 2050. Cet objectif ambitieux peut être atteint grâce à différentes stratégies d'atténuation des GES, telles que l'électrification, les changements de comportement des consommateurs, l'amélioration de l'efficacité énergétique des procédés, l'utilisation de substituts aux combustibles fossiles (tels que la bioénergie ou l'hydrogène), le captage et le stockage du carbone (CSC), entre autres. Cette thèse vise à contribuer à deux de ces stratégies : le covoiturage (qui appartient à la catégorie des changements de comportement du consommateur) et la capture et le stockage du carbone. Cette thèse fournit des modèles mathématiques et d'optimisation et des algorithmes pour la planification opérationnelle et tactique des systèmes de covoiturage, et des heuristiques pour la planification stratégique d'un réseau de captage et de stockage du carbone. Dans le covoiturage, les émissions sont réduites lorsque les individus voyagent ensemble au lieu de conduire seuls. Dans ce contexte, cette thèse fournit de nouveaux modèles mathématiques pour représenter les systèmes de covoiturage, allant des problèmes d'affectation stochastique à deux étapes aux problèmes d'empaquetage d'ensembles stochastiques à deux étapes qui peuvent représenter un large éventail de systèmes de covoiturage. Ces modèles aident les décideurs dans leur planification opérationnelle des covoiturages, où les conducteurs et les passagers doivent être jumelés pour le covoiturage à court terme. De plus, cette thèse explore la planification tactique des systèmes de covoiturage en comparant différents modes de fonctionnement du covoiturage et les paramètres de la plateforme (par exemple, le partage des revenus et les pénalités). De nouvelles caractéristiques de problèmes sont étudiées, telles que l'incertitude du conducteur et du passager, la flexibilité de réappariement et la réservation de l'offre de conducteur via les frais de réservation et les pénalités. En particulier, la flexibilité de réappariement peut augmenter l'efficacité d'une plateforme de covoiturage, et la réservation de l'offre de conducteurs via les frais de réservation et les pénalités peut augmenter la satisfaction des utilisateurs grâce à une compensation garantie si un covoiturage n'est pas fourni. Des expériences computationnelles détaillées sont menées et des informations managériales sont fournies. Malgré la possibilité de réduction des émissions grâce au covoiturage et à d'autres stratégies d'atténuation, des études macroéconomiques mondiales montrent que même si plusieurs stratégies d'atténuation des GES sont utilisées simultanément, il ne sera probablement pas possible d'atteindre des émissions nettes nulles d'ici 2050 sans le CSC. Ici, le CO2 est capturé à partir des sites émetteurs et transporté vers des réservoirs géologiques, où il est injecté pour un stockage à long terme. Cette thèse considère un problème de planification stratégique multipériode pour l'optimisation d'une chaîne de valeur CSC. Ce problème est un problème combiné de localisation des installations et de conception du réseau où une infrastructure CSC est prévue pour les prochaines décennies. En raison des défis informatiques associés à ce problème, une heuristique est introduite, qui est capable de trouver de meilleures solutions qu'un solveur commercial de programmation mathématique, pour une fraction du temps de calcul. Cette heuristique comporte des phases d'intensification et de diversification, une génération améliorée de solutions réalisables par programmation dynamique, et une étape finale de raffinement basée sur un modèle restreint. Dans l'ensemble, les contributions de cette thèse sur le covoiturage et le CSC fournissent des modèles de programmation mathématique, des algorithmes et des informations managériales qui peuvent aider les praticiens et les parties prenantes à planifier des émissions nettes nulles.With the ratification of the Paris Agreement, countries committed to limiting global warming to well below 2, preferably to 1.5 degrees Celsius, compared to pre-industrial levels. To this end, anthropogenic greenhouse gas (GHG) emissions (such as CO2) must be reduced to reach net-zero carbon emissions by 2050. This ambitious target may be met by means of different GHG mitigation strategies, such as electrification, changes in consumer behavior, improving the energy efficiency of processes, using substitutes for fossil fuels (such as bioenergy or hydrogen), and carbon capture and storage (CCS). This thesis aims at contributing to two of these strategies: ridesharing (which belongs to the category of changes in consumer behavior) and carbon capture and storage. This thesis provides mathematical and optimization models and algorithms for the operational and tactical planning of ridesharing systems, and heuristics for the strategic planning of a carbon capture and storage network. In ridesharing, emissions are reduced when individuals travel together instead of driving alone. In this context, this thesis provides novel mathematical models to represent ridesharing systems, ranging from two-stage stochastic assignment problems to two-stage stochastic set packing problems that can represent a wide variety of ridesharing systems. These models aid decision makers in their operational planning of rideshares, where drivers and riders have to be matched for ridesharing on the short-term. Additionally, this thesis explores the tactical planning of ridesharing systems by comparing different modes of ridesharing operation and platform parameters (e.g., revenue share and penalties). Novel problem characteristics are studied, such as driver and rider uncertainty, rematching flexibility, and reservation of driver supply through booking fees and penalties. In particular, rematching flexibility may increase the efficiency of a ridesharing platform, and the reservation of driver supply through booking fees and penalties may increase user satisfaction through guaranteed compensation if a rideshare is not provided. Extensive computational experiments are conducted and managerial insights are given. Despite the opportunity to reduce emissions through ridesharing and other mitigation strategies, global macroeconomic studies show that even if several GHG mitigation strategies are used simultaneously, achieving net-zero emissions by 2050 will likely not be possible without CCS. Here, CO2 is captured from emitter sites and transported to geological reservoirs, where it is injected for long-term storage. This thesis considers a multiperiod strategic planning problem for the optimization of a CCS value chain. This problem is a combined facility location and network design problem where a CCS infrastructure is planned for the next decades. Due to the computational challenges associated with that problem, a slope scaling heuristic is introduced, which is capable of finding better solutions than a state-of-the-art general-purpose mathematical programming solver, at a fraction of the computational time. This heuristic has intensification and diversification phases, improved generation of feasible solutions through dynamic programming, and a final refining step based on a restricted model. Overall, the contributions of this thesis on ridesharing and CCS provide mathematical programming models, algorithms, and managerial insights that may help practitioners and stakeholders plan for net-zero emissions

Assessment of masticatory function and nutrition in people with dental implants

Background: Treatment with bimaxillary implant-supported fixed prostheses is the state-of-the-art treatment of complete edentulism and replacement of natural teeth. However, the extraction of teeth results in the loss of periodontal mechanoreceptors (PMRs), normally located in the periodontal ligament. Complete edentulism implies a total absence of PMRs. The total lack of input from PMRs, which is involved in encoding relevant aspects such as the magnitude of biting forces, makes this group unique. The complete retaining of the prostheses and optimised restored function, anatomy, and aesthetics, mostly to the great satisfaction of the patient, make the group even more unique and interesting. However, the literature lacks studies assessing masticatory function and nutrition in completely edentulous people treated with bimaxillary implant-supported fixed prostheses. In fact, compared to other prosthetic treatments, such as hip and knee joint replacements, assessment routines for the outcomes of implant treatments are rare. The subjective and objective evaluations of masticatory function and assessment of nutritional status, nutritional risk and eating habits could be key factors for optimising masticatory function in people treated with implants. Objectives: The thesis aims to assess the masticatory function and nutrition in people treated with bimaxillary implant-supported fixed prostheses compared to people with natural dentitions. Identifying differences and similarities between the groups may clarify functional impairments, nutritional deficiencies, and risks. Material and methods: The thesis focuses on assessing various aspects of masticatory function and nutrition in people treated with bimaxillary implant-supported fixed prostheses compared to a control group of people with natural dentitions. Study I focuses on the establishment of a protocol/methodology for assessment of masticatory performance using a hard viscoelastic test food. Study II focuses on that agreement between the established objective measure of masticatory performance with a subjective evaluation of functional limitations and quality of life. Study III evaluates nutritional measures in people with bimaxillary implant-supported fixed prostheses. Nutritional status, nutritional risk and eating habits are assessed in comparison to an equivalent control group of people with natural dentition. Results: The overall results of the three studies reveal significant differences between the groups. The masticatory performance is significantly lower in people treated with bimaxillary implant-supported fixed prostheses (Studies I & II). However, there is no correlation between the objective indicators of masticatory performance and the subjective measures of any major limitation in function or quality of life (Study II). The differences are, however, present when analysing nutritional status, nutritional risk and eating habits (Study III). The participants in the implant group exhibited a significantly lesser variety of consumed food and a higher risk of malnutrition. Body Mass Index (BMI) was significantly higher and in the overweight range compared to normal weight in the control group. The risk of nutritional deficiency was significantly higher among participants with bimaxillary implant-supported fixed prostheses and in the range of high compared to moderate in the control group. Conclusion: The success of treatment with bimaxillary implant-supported fixed prostheses, considered state-of-the-art treatment, is reflected in subjective measures of patient- reported satisfaction and high oral health-related quality of life. However, the masticatory performance is significantly impaired. Eating habits and nutritional status can be negatively affected, resulting in an increased risk of nutritional deficiencies and malnutrition

Tetraspanin web formation and function

The cell membrane is crucial for living cells; it encloses the intracellular matrix, maintains the concentration of cytosolic components, and controls the in-/outward signalling and interaction pathways. The cell membrane consists mainly of lipids and proteins. Membrane proteins are involved in essential physiological functions of the cell; in addition, they have the ability to organize, interact and assemble laterally to form clusters or platforms that are biologically important for cell function. The mechanisms underlying membrane protein organization and assembly in clusters are still not completely understood. Tetraspanins are a family of membrane proteins exhibiting a particularly high propensity to interact with each other or with partner proteins to form so-called tetraspanin enriched microdomains (TEM) or tetraspanin webs. TEMs are involved in pathogen infections, creating entry and exit platforms, and promote different stages of cancer. Until now, the mechanism of TEM assembly is poorly understood. All tetraspanin family members share a similar molecular structure that comprises four transmembrane domains, intracellular N- and C-termini, a very short intracellular loop, a small extracellular loop (SEL), and a large extracellular loop (LEL), which is further subdivided in five helical domains, the α-, β-, γ-, δ- and ε-domain. CD81 is an ubiquitously expressed tetraspanin; it is the best studied tetraspanin and one of the most important family members. CD81 plays a crucial role in TEM building and can form with its partner proteins large tetraspanin webs that play physiological roles in different cellular functions and regulate diverse cellular processes. Here, I examined which part of the CD81 molecule is required for protein clustering and protein organization leading to formation of tetraspanin microdomains in the plasma membrane of T cells and hepatocytes. Astonishingly, I find that the organization and assembly of large CD81 platforms are driven by the short extracellular δ-domain of CD81-LEL, independent from the strong primary interactions with partner proteins as well as the secondary weak stabilizing interactions mediated by palmitoylation. Moreover, the δ-domain is not only necessary for protein clustering but it is also essential for platform function and viral entry. Here, a new model of tetraspanin web formation was presented, in which the δ-domain plays the key role for protein clustering, tetraspanin web organization and function. This model is based on specific interactions via the δ-domain, possibly including a protein dimerization step, to control the organization of tetraspanins into large webs and to regulate their function, instead of stable binary interactions as described by the classical view of TEM organization.Tetraspanin Web Bildung und Funktion Die Zellmembran ist unabdingbar für lebendige Zellen; sie umschließt die intrazelluläre Matrix, reguliert die Konzentration zytosolischer Komponenten, und kontrolliert die in-/auswärtigen Signale und Interaktionswege. Die Zellmembran besteht hauptsächlich aus Lipiden und Proteinen. Die Membranproteine sind in essenzielle physiologische Funktionen der Zelle involviert; zudem haben sie die Fähigkeit sich zu organisieren, miteinander zu interagieren und zu assemblieren, um Cluster oder Plattformen zu bilden, welche für die biologischen Funktionen der Zelle wichtig sind. Die Mechanismen, die die Proteinorganisation und die Assemblierung zu Clustern steuern, sind noch nicht vollständig verstanden. Tetraspanine sind eine Familie der Membranproteine, die eine hohe Tendenz haben mit sich selbst und mit anderen Proteinpartnern zu interagieren, um sogenannte Tetraspanin angereicherte Microdomänen (TEM) oder Tetraspaninnetzwerke zu bilden. TEMs spielen eine Rolle bei Infektionen, u.a. indem sie bei der Bildung von Zugangs- und Ausgangsplattformen mitwirken, sowie bei der Steuerung verschiedener Krebsphasen. Aktuell ist der TEM-Bildungsmechanismus nur unzureichend aufgeklärt. Alle Tetraspaninfamilienmitglieder haben eine ähnliche molekulare Struktur gemein, die vier Transmembrandomänen, intrazelluläre N- und C-Termini, eine sehr kleine intrazelluläre Schleife, eine kleine extrazelluläre Schleife (SEL), und eine große extrazelluläre Schleife (LEL) beinhaltet. Die große extrazelluläre Schleife ist weiter in fünf helikale Domänen, die α-, β-, γ-, δ- und ε-Domäne, unterteilt. CD81 ist ein ubiquitär exprimiertes Tetraspanin; es ist das am intensivsten untersuchte Tetraspanin und eines der wichtigsten Familienmitglieder. CD81 spielt eine wichtige Rolle bei der TEM-Bildung und kann mit anderen Proteinpartnern große Tetraspaninnetzwerke ausbilden, die physiologische Rollen in verschiedenen zellulären Funktionen spielen und diverse zelluläre Prozessen regulieren. Hier habe ich untersucht, welcher Teil des CD81 Moleküls für die Bildung von Proteinclustern notwendig ist, die die Vorrausetzung für Tetraspanin-Mikrodomänen in der Plasmamembran von T-Zellen und Hepatozyten darstellt. Erstaunlicherweise zeigte sich, dass die Organisation der großen CD81-Plattformen von der kleinen extrazellulären δ-Domäne des CD81-LEL Moleküls gesteuert wird. Zudem ist dieser Effekt der δ-Domäne unabhängig von starken primären Interaktionen mit Proteinpartnern sowie von den schwächeren sekundären stabilisierenden Interaktionen die durch Palmitoylierung ermittelt werden. Außerdem ist die δ-Domäne nicht nur für die Bildung von Proteinclustern notwendig, sondern auch für die Funktionsfähigkeit der Plattformen und für Vireninfektionen erforderlich. In dieser Arbeit wird ein neues Modell für die Bildung von Tetraspaninnetzwerken vorgestellt, in dem die δ-Domäne eine Schlüsselrolle bei der Bildung von Proteinclustern und bei der Organisation und Funktionsfähigkeit der Tetraspaninnetzwerke spielt. Dieses Modell basiert auf spezifischen Interaktionen der δ-Domäne und einem potenziellen CD81 Dimerisierungsschritt, welche die Organisierung von Tetraspaninen innerhalb großer Netzwerke kontrollieren und deren Funktionen regulieren im Gegensatz zum klassischen Modell in dem stabile binäre Interaktionen die Organisation von TEMs dominieren

Acoustical characterization and parameter optimization of polymeric noise control materials

The sound transmission loss (STL) characteristics of polymer-based materials are considered. Analytical models that predict, characterize and optimize the STL of polymeric materials, with respect to physical parameters that affect performance, are developed for single layer panel configuration and adapted for layered panel construction with homogenous core. An optimum set of material parameters is selected and translated into practical applications for validation. Sound attenuating thermoplastic materials designed to be used as barrier systems in the automotive and consumer industries have certain acoustical characteristics that vary in function of the stiffness and density of the selected material. The validity and applicability of existing theory is explored, and since STL is influenced by factors such as the surface mass density of the panel\u27s material, a method is modified to improve STL performance and optimize load-bearing attributes. An experimentally derived function is applied to the model for better correlation. In-phase and out-ofphase motion of top and bottom layers are considered. It was found that the layered construction of the coinjection type would exhibit fused planes at the interface and move in-phase. The model for the single layer case is adapted to the layered case where it would behave as a single panel. Primary physical parameters that affect STL are identified and manipulated. Theoretical analysis is linked to the resin\u27s matrix attribute. High STL material with representative characteristics is evaluated versus standard resins. It was found that high STL could be achieved by altering materials\u27 matrix and by integrating design solution in the low frequency range. A suggested numerical approach is described for STL evaluation of simple and complex geometries. In practice, validation on actual vehicle systems proved the adequacy of the acoustical characterization process

The Influence of 'Free' Marketing Websites on the Brand Equity from the Perspective of Major Manufacturing Entities

Technology and internet seems to control the processes of the business environment specifically through the last two decades. Now, most organizations are depending on technology and internet to reach to its goals and ambitions through focusing on online marketing with all its aspects and potentials. There are many types of online marketing among them is the idea of free marketing which an approach that is used to promote goods and services without any financial demands. Usually this type of marketing takes place through the social media websites and other websites that involves social interaction. The results of the study indicated that there is a positively significant influence of free marketing on brand equity also; free marketing appeared to be influential in a positive way not only for regular brands but also for luxurious brands as it helps the brand reaches for as many customers as possible. However, the study results noted that there appeared to be a good level of awareness of the importance of social media marketing among the sample of the study and the industrial sector in Jordan appeared to be reliable to a certain degree of the idea of free marketing through social media websites including (Facebook, twitter, Google+, instagram and LinkedIn). Keywords: Online marketing, free marketing, brand equity, B2C business, Marketing Strateg

Qatarization success Factors: A framework for organizations and policymakers

State of Qatar has recently witnessed substantial economic growth. Responding to the rapidly increasing business activity, an influx of expatriate workers has been filling the gap between the limited supply and the large demand of skilled and unskilled workers. Faced with the challenge of sustaining its economy on the long run as well as preserving its national identity and culture, Qatar has sought to introduce and implement a workforce nationalization strategy called Qatarization. Given the interdisciplinary nature of the issue, many factors come to play in impacting the success of a Qatarization program at both the macro-level and the micro-level. This paper aims to highlight the factors that have the most impact on the success of a Qatarization program being executed at the organizational level. First, a literature review was focused on highlighting different factors and aspects that has been discussed or featured in previous studies from a variety of fields and disciplines. After executing four in-depth interviews with Qatarization experts, a Qatarization Success Factors model was developed containing 19 different aspects that were believed to have an impact on the success of a Qatarization program. Those aspects were categorized according to whether they fall under the direct influence (internal aspects) or indirect influence (external aspects) of an organization executing a Qatarization program. A self-administrated structured questionnaire was then developed and distributed electronically targeting professionals in Qatar with experiences related to human resources, learning and development, management, or Qatarization. Respondents were asked to rate 19 different statements, each related to an aspect of the model, using a 7-point Likert Scale. A total of 153 qualified responses were successfully collected and then analyzed using factors analysis. Upon performing the analysis, a total of five factors were extracted and then ranked according to the percentage of variances explained. The findings of this paper found that factors and aspects related to internal organizational factors had the most impact on the success of the Qatarization program. Next to that were factors related to the national educational structures, followed by national policies, economic regulations, and social and cultural factors respectively