Operations management for double-ended queues

In this paper we have presented the double-ended queueing model with its generic form, abstract modeling extensions, different types of controls to be assumed by the management of the system, as well as optimization via various methodologies. Since its inception in 1950s, double-ended queuing model has had widespread use and recently it is observed that literature is focusing on social welfare perspectives on queues under strategically acting customers and enhanced information exchange due to advanced technology. It is also reviewed that for the complex and analytically tractable versions of double-ended queues it is possible to obtain approximate or near-optimal results via methodologies such as simulation and fluid and diffusion approximations.No sponso

A Microscopic Simulation Laboratory for Evaluation of Off-street Parking Systems

The parking industry produces an enormous amount of data every day that, properly analyzed, will change the way the industry operates. The collected data form patterns that, in most cases, would allow parking operators and property owners to better understand how to maximize revenue and decrease operating expenses and support the decisions such as how to set specific parking policies (e.g. electrical charging only parking space) to achieve the sustainable and eco-friendly parking. However, there lacks an intelligent tool to assess the layout design and operational performance of parking lots to reduce the externalities and increase the revenue. To address this issue, this research presents a comprehensive agent-based framework for microscopic off-street parking system simulation. A rule-based parking simulation logic programming model is formulated. The proposed simulation model can effectively capture the behaviors of drivers and pedestrians as well as spatial and temporal interactions of traffic dynamics in the parking system. A methodology for data collection, processing, and extraction of user behaviors in the parking system is also developed. A Long-Short Term Memory (LSTM) neural network is used to predict the arrival and departure of the vehicles. The proposed simulator is implemented in Java and a Software as a Service (SaaS) graphic user interface is designed to analyze and visualize the simulation results. This study finds the active capacity of the parking system, which is defined as the largest number of actively moving vehicles in the parking system under the facility layout. In the system application of the real world testbed, the numerical tests show (a) the smart check-in device has marginal benefits in vehicle waiting time; (b) the flexible pricing policy may increase the average daily revenue if the elasticity of the price is not involved; (c) the number of electrical charging only spots has a negative impact on the performance of the parking facility; and (d) the rear-in only policy may increase the duration of parking maneuvers and reduce the efficiency during the arrival rush hour. Application of the developed simulation system using a real-world case demonstrates its capability of providing informative quantitative measures to support decisions in designing, maintaining, and operating smart parking facilities

New Challenges in Quality of Services Control Architectures in Next Generation Networks

A mesura que Internet i les xarxes IP s'han anat integrant dins la societat i les corporacions, han anat creixent les expectatives de nous serveis convergents així com les expectatives de qualitat en les comunicacions. Les Next Generation Networks (NGN) donen resposta a les noves necessitats i representen el nou paradigma d'Internet a partir de la convergència IP. Un dels aspectes menys desenvolupats de les NGN és el control de la Qualitat del Servei (QoS), especialment crític en les comunicacions multimèdia a través de xarxes heterogènies i/o de diferents operadors. A més a més, les NGN incorporen nativament el protocol IPv6 que, malgrat les deficiències i esgotament d'adreces IPv4, encara no ha tingut l'impuls definitiu.Aquesta tesi està enfocada des d'un punt de vista pràctic. Així doncs, per tal de poder fer recerca sobre xarxes de proves (o testbeds) que suportin IPv6 amb garanties de funcionament, es fa un estudi en profunditat del protocol IPv6, del seu grau d'implementació i dels tests de conformància i interoperabilitat existents que avaluen la qualitat d'aquestes implementacions. A continuació s'avalua la qualitat de cinc sistemes operatius que suporten IPv6 mitjançant un test de conformància i s'implementa el testbed IPv6 bàsic, a partir del qual es farà la recerca, amb la implementació que ofereix més garanties.El QoS Broker és l'aportació principal d'aquesta tesi: un marc integrat que inclou un sistema automatitzat per gestionar el control de la QoS a través de sistemes multi-domini/multi-operador seguint les recomanacions de les NGN. El sistema automatitza els mecanismes associats a la configuració de la QoS dins d'un mateix domini (sistema autònom) mitjançant la gestió basada en polítiques de QoS i automatitza la negociació dinàmica de QoS entre QoS Brokers de diferents dominis, de forma que permet garantir QoS extrem-extrem sense fissures. Aquesta arquitectura es valida sobre un testbed de proves multi-domini que utilitza el mecanisme DiffServ de QoS i suporta IPv6.L'arquitectura definida en les NGN permet gestionar la QoS tant a nivell 3 (IP) com a nivell 2 (Ethernet, WiFi, etc.) de forma que permet gestionar també xarxes PLC. Aquesta tesi proposa una aproximació teòrica per aplicar aquesta arquitectura de control, mitjançant un QoS Broker, a les noves xarxes PLC que s'estan acabant d'estandarditzar, i discuteix les possibilitats d'aplicació sobre les futures xarxes de comunicació de les Smart Grids.Finalment, s'integra en el QoS Broker un mòdul per gestionar l'enginyeria del tràfic optimitzant els dominis mitjançant tècniques de intel·ligència artificial. La validació en simulacions i sobre un testbed amb routers Cisco demostra que els algorismes genètics híbrids són una opció eficaç en aquest camp.En general, les observacions i avenços assolits en aquesta tesi contribueixen a augmentar la comprensió del funcionament de la QoS en les NGN i a preparar aquests sistemes per afrontar problemes del món real de gran complexitat.A medida que Internet y las redes IP se han ido integrando dentro de la sociedad y las corporaciones, han ido creciendo las expectativas de nuevos servicios convergentes así como las expectativas de calidad en las comunicaciones. Las Next Generation Networks (NGN) dan respuesta a las nuevas necesidades y representan el nuevo paradigma de Internet a partir de la convergencia IP. Uno de los aspectos menos desarrollados de las NGN es el control de la Calidad del Servicio (QoS), especialmente crítico en las comunicaciones multimedia a través de redes heterogéneas y/o de diferentes operadores. Además, las NGN incorporan nativamente el protocolo IPv6 que, a pesar de las deficiencias y agotamiento de direcciones IPv4, aún no ha tenido el impulso definitivo.Esta tesis está enfocada desde un punto de vista práctico. Así pues, con tal de poder hacer investigación sobre redes de prueba (o testbeds) que suporten IPv6 con garantías de funcionamiento, se hace un estudio en profundidad del protocolo IPv6, de su grado de implementación y de los tests de conformancia e interoperabilidad existentes que evalúan la calidad de estas implementaciones. A continuación se evalua la calidad de cinco sistemas operativos que soportan IPv6 mediante un test de conformancia y se implementa el testbed IPv6 básico, a partir del cual se realizará la investigación, con la implementación que ofrece más garantías.El QoS Broker es la aportación principal de esta tesis: un marco integrado que incluye un sistema automatitzado para gestionar el control de la QoS a través de sistemas multi-dominio/multi-operador siguiendo las recomendaciones de las NGN. El sistema automatiza los mecanismos asociados a la configuración de la QoS dentro de un mismo dominio (sistema autónomo) mediante la gestión basada en políticas de QoS y automatiza la negociación dinámica de QoS entre QoS brokers de diferentes dominios, de forma que permite garantizar QoS extremo-extremo sin fisuras. Esta arquitectura se valida sobre un testbed de pruebas multi-dominio que utiliza el mecanismo DiffServ de QoS y soporta IPv6. La arquitectura definida en las NGN permite gestionar la QoS tanto a nivel 3 (IP) o como a nivel 2 (Ethernet, WiFi, etc.) de forma que permite gestionar también redes PLC. Esta tesis propone una aproximación teórica para aplicar esta arquitectura de control, mediante un QoS Broker, a las noves redes PLC que se están acabando de estandardizar, y discute las posibilidades de aplicación sobre las futuras redes de comunicación de las Smart Grids.Finalmente, se integra en el QoS Broker un módulo para gestionar la ingeniería del tráfico optimizando los dominios mediante técnicas de inteligencia artificial. La validación en simulaciones y sobre un testbed con routers Cisco demuestra que los algoritmos genéticos híbridos son una opción eficaz en este campo.En general, las observaciones y avances i avances alcanzados en esta tesis contribuyen a augmentar la comprensión del funcionamiento de la QoS en las NGN y en preparar estos sistemas para afrontar problemas del mundo real de gran complejidad.The steady growth of Internet along with the IP networks and their integration into society and corporations has brought with it increased expectations of new converged services as well as greater demands on quality in communications. The Next Generation Networks (NGNs) respond to these new needs and represent the new Internet paradigm from the IP convergence. One of the least developed aspects in the NGNs is the Quality of Service (QoS) control, which is especially critical in the multimedia communication through heterogeneous networks and/or different operators. Furthermore, the NGNs natively incorporate the IPv6 protocol which, despite its shortcomings and the depletion of IPv4 addresses has not been boosted yet.This thesis has been developed with a practical focus. Therefore, with the aim of carrying out research over testbeds supporting the IPv6 with performance guarantees, an in-depth study of the IPv6 protocol development has been conducted and its degree of implementation and the existing conformance and interoperability tests that evaluate these implementations have been studied. Next, the quality of five implementations has been evaluated through a conformance test and the basic IPv6 testbed has been implemented, from which the research will be carried out. The QoS Broker is the main contribution to this thesis: an integrated framework including an automated system for QoS control management through multi-domain/multi-operator systems according to NGN recommendations. The system automates the mechanisms associated to the QoS configuration inside the same domain (autonomous system) through policy-based management and automates the QoS dynamic negotiation between peer QoS Brokers belonging to different domains, so it allows the guarantee of seamless end-to-end QoS. This architecture is validated over a multi-domain testbed which uses the QoS DiffServ mechanism and supports IPv6.The architecture defined in the NGN allows QoS management at level 3 (IP) as well as at level 2 (e.g. Ethernet, WiFi) so it also facilitates the management of PLC networks. Through the use of a QoS Broker, this thesis proposes a theoretical approach for applying this control architecture to the newly standardized PLC networks, and discusses the possibilities of applying it over the future communication networks of the Smart Grids.Finally, a module for managing traffic engineering which optimizes the network domains through artificial intelligence techniques is integrated in the QoS Broker. The validations by simulations and over a Cisco router testbed demonstrate that hybrid genetic algorithms are an effective option in this area.Overall, the advances and key insights provided in this thesis help advance our understanding of QoS functioning in the NGNs and prepare these systems to face increasingly complex problems, which abound in current industrial and scientific applications

Reinforcement Learning

Brains rule the world, and brain-like computation is increasingly used in computers and electronic devices. Brain-like computation is about processing and interpreting data or directly putting forward and performing actions. Learning is a very important aspect. This book is on reinforcement learning which involves performing actions to achieve a goal. The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional, hand-designed, non-learning controllers. As learning computers can deal with technical complexities, the tasks of human operators remain to specify goals on increasingly higher levels. This book shows that reinforcement learning is a very dynamic area in terms of theory and applications and it shall stimulate and encourage new research in this field

Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

Liquid decision making

In today’s business world, decisions have to be made on different levels, including strategic, tactical, and operational levels. Decisions on the strategic level are characterized by their complexity, longevity and impact. Such decisions can benefit from the participation of a large, diverse group of people as they contribute different background knowledge, perspectives, and evaluation criteria. Typically, such decisions need to be considered over a prolonged period of time as opinions may need to be formed or may change due to the availability of new information. The goal of people in group decision making situations is typically to achieve good decisions. A mechanism is thus desirable that is capable of addressing the aforementioned challenges and of producing a good decision. For this work, a decision is thought to be good if it is predominantly based on the sincere opinions of the participants. In this thesis, we investigate the market metaphor as a promising approach for group decision making. Markets are attributed with the capability of gathering and aggregating assessments from people in a single indicator, the price. They allow for a continued participation over a prolonged time, reversibility of one’s market position by repeated trading, and the usage of individual evaluation criteria. For investigating the application of the market metaphor to decision making, we develop LDM, a market-based approach for group decision making. There, we represent a pending decision as a market and the decision options as stocks. Participants then buy shares of their favored stocks and sell shares of the stocks they dislike. High demand leads to price increase whereas low prices are the result of low demand. The most favored decision options can be identified from the ranking of the stocks according to their prices. To support the achievement of a good decision, we model the market behavior of participants, devise design principles, identify suitable application scenarios, and determine appropriate functionalities for a market software. We furthermore devise the concept of market perturbations for uncovering the trading intentions of participants. We furthermore implement a web-based software prototype of LDM. It provides functionalities for decision making, market trading, user handling, information exchange, and market perturbations. Participants there trade their favored stocks using virtual play money. We test the LDM approach and its software prototype in an EU-funded project, in a lab study, in the selection of research proposals, and in a university seminar for scenario building.Entscheidungen müssen in Unternehmen auf unterschiedlichen Ebenen getroffen werden. Besonders strategische Entscheidungen sind oft komplex, langwierig und haben weitreichende Auswirkungen. Die Beteiligung einer großen, heterogenen Personengruppe kann solche Entscheidungen begünstigen, da sie unterschiedliches Hintergrundwissen sowie verschiedene Perspektiven und Bewertungskriterien beisteuern. Oft werden solche Entscheidungen über einen längeren Zeitraum getroffen, da die Beteiligten sich ihre Meinungen erst bilden müssen, oder diese sich durch neue Informationen ändern. Um dabei gute Entscheidungen zu treffen, sollte ein Ansatz dazu unter den geschilderten Umständen ein gutes Ergebnis liefern können. Als gutes Ergebnis wird in dieser Arbeit eine Entscheidung angesehen, die hauptsächlich auf der ehrlichen Meinung der Teilnehmer beruht. In dieser Arbeit untersuchen wir die Marktmetapher als vielversprechenden Ansatz für die Entscheidungsfindung. Märkten wird die Fähigkeit zugeschrieben, Informationen von verschiedenen Personen in einem einzigen Indikator, dem Preis, aggregieren zu können. Sie ermöglichen dabei eine kontinuierliche Teilnahme über einen längeren Zeitraum, eine Änderung der Meinung durch wiederholtes Handeln sowie die Anwendung von individuellen Bewertungskriterien. Für unsere Untersuchung entwickeln wir LDM, einen marktbasierten Ansatz für die Entscheidungsfindung in Gruppen. Eine anstehende Entscheidung wird darin als Markt repräsentiert und die Entscheidungsoptionen als Aktien. Die Teilnehmer kaufen Anteile ihrer favorisierten Aktien und verkaufen die Anderen mittels virtuellem Spielgeld. Eine hohe Nachfrage führt zu hohen Preisen, niedrige Nachfrage zu niedrigen Preisen. Aus der Rangfolge der Aktien nach ihren Preisen kann dann die bevorzugteste Entscheidungsoption identifiziert werden. Um eine gute Entscheidung mittels \acl{LDM} zu erreichen, erstellen wir ein Verhaltensmodell der Teilnehmer, Entwurfsprinzipien, geeignete Einsatzszenarien und geeignete Funktionalitäten für eine Software. Außerdem entwickeln wir das Konzept der Marktstörungen um Handelsintentionen der Teilnehmer in Erfahrung zu bringen. Diese Aspekte setzen wir in einer webbasierten Software um, die Funktionalitäten zur Entscheidungsfindung, zum Handeln, zur Nutzerverwaltung, zum Informationsaustausch und für Marktstörungen enthält. LDM sowie die Sofware testen wir erfolgreich in einem EU-Projekt, in einer Laborstudie, bei der Auswahl von Forschungsvorhaben und in einem Universitätsseminar zu Szenarioentwicklung

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017