The thesis is focused on the optimization of models of transportation and transshipment problem with random demand, additional edges, and dynamic pricing. The theoretical part of the thesis introduces mathematical models of transportation. The software GAMS, which is used for the solution, is all so described. The practical part is a split among chapters and implements the described models by using real data.

It is commonly agreed among energy experts that smart meters (SMs) are the key component that will facilitate the transition towards the smart grid. Fast-peace innovations in the smart metering infrastructure (AMI) are exposing countless benefits that network operators can obtain when they integrate SMs applications into their daily operations.  Following the amendment in 2017, where the Swedish government dictated that all SMs should now include new features such as remote control, higher time resolution for the energy readings and a friendly interface for customers to access their own data; network operators in Sweden are currently replacing their SMs for a new model, also called the second generation of SMs. While the replacement of meters is in progress, many utilities like Hemab are trying to reveal which technical and financial benefits the new generation of SMs will bring to their operations.    As a first step, this thesis presents the results of a series of interviews carried out with different network operators in Sweden. It is studied which functionalities have the potential to succeed in the near future, as well as those functionalities that are already being tested or fully implemeneted by some utilities in Sweden. Furthermore, this thesis analyses those obstacles and barriers that utilities encounter when trying to implement new applications using the new SMs. In a second stage, an alarm system for power interruptions and voltage-quality events (e.g., overvoltage and undervoltage) using VisionAir software and OMNIPOWER 3-phase meters is evaluated. The results from the evaluation are divided into three sections: a description of the settings and functionalities of the alarm, the outcomes from the test, and a final discussion of potential applications. This study has revealed that alarm functions, data analytics (including several methods such as load forecasting, customer segmentation and non-technical losses analysis), power quality monitoring, dynamic pricing, and load shedding have the biggest potential to succeed in Sweden in the coming years. Furthermore, it can be stated that the lack of time, prioritization of other projects in the grid and the integration of those new applications into the current system seem to be the main barrier for Swedish utilities nowadays. Regarding the alarm system, it was found that the real benefits for network operators arrive when the information coming from an alarm system is combined with a topology interface of the network and a customer notifications server. Both applications could improve customer satisfaction by significantly reducing outage time and providing customers with real-time and precise information about the problems in the grid.

As urban population across the globe increases, the demand for adequate transportation grows. Several strategies have been suggested as a solution to the congestion which results from this high demand outpacing the existing supply of transportation facilities. High –Occupancy Toll (HOT) lanes have become increasingly more popular as a feature on today’s highway system. The I-95 Express HOT lane in Miami Florida, which is currently being expanded from a single Phase (Phase I) into two Phases, is one such HOT facility. With the growing abundance of such facilities comes the need for indepth study of demand patterns and development of an appropriate pricing scheme which reduces congestion. This research develops a method for dynamic pricing on the I-95 HOT facility such as to minimize total travel time and reduce congestion. We apply non-linear programming (NLP) techniques and the finite difference stochastic approximation (FDSA), genetic algorithm (GA) and simulated annealing (SA) stochastic algorithms to formulate and solve the problem within a cell transmission framework. The solution produced is the optimal flow and optimal toll required to minimize total travel time and thus is the system-optimal solution. We perform a comparative evaluation of FDSA, GA and SA non-linear programming algorithms used to solve the NLP and the ANOVA results show that there are differences in the performance of the NLP algorithms in solving this problem and reducing travel time. We then conclude by demonstrating that econometric iv forecasting methods utilizing vector autoregressive (VAR) techniques can be applied to successfully forecast demand for Phase 2 of the 95 Express which is planned for 2014

Several studies have been conducted within machine learning, and various variations have been applied to a wide spectrum of other fields. However, a thorough feasibility study within the payment processing industry using machine learning classifier algorithms is yet to be explored. Here, we construct a rule-based response vector and use that in combination with a magnitude of varying feature vectors across different machine learning classifier algorithms to try and determine whether individual transactions can be considered profitable from a business point of view. These algorithms include Naive-Bayes, AdaBoosting, Stochastic Gradient Descent, K-Nearest Neighbors, Decision Trees and Random Forests, all helped us build a model with a high performance that acts as a robust confirmation of both the benefits and a theoretical guide on the implementation of machine learning algorithms in the payment processing industry. The results as such are a firm confirmation on the benefits of data intensive models, even in complex industries similar to Swedbank Pay’s. These Implications help further boost innovation and revenue as they offer a better understanding of the current pricing mechanisms. / Många studier har utförts inom ämnet maskininlärning, och olika variationer har applicerats på ett brett spektrum av andra ämnen. Däremot, så har en ordentlig genomförbarhetsstudie inom betalningsleveransindustrin med hjälp av klassificeringsalgortimer har ännu ej utforskats. Här har vi konstruerat en regelbaserad responsvektor och använt den, tillsammans med en rad olika och varierande egenskapvektorer på olika maskininlärningsklassificeringsalgoritmer för att försöka avgöra ifall individuella transaktioner är lönsamma utifrån företagets perspektiv. Dessa algoritmer är Naive-Bayes, AdaBoosting, Stokastisk gradient medåkning, K- Närmaste grannar, beslutsträd och slumpmässiga beslutsskogar. Alla dessa har hjälpt oss bygga en teoretisk vägledning om implementering av maskininlärningsalgoritmer inom betalningsleveransindustrin. Dessa resultat är en robust bekräftelse på fördelarna av dataintensiva modeller även inom sådana komplexa industrier Swedbank Pay är verksamma inom. Implikationerna hjälper vidare att förstärka innovationen och öka intäkterna eftersom de erbjuder en bättre förståelse för deras nuvarande prissättningsmekanism.

Diese Dissertation besteht aus drei unabhängigen Kapiteln in den Bereichen Matching Market Design, Industrieökonomie und Wettbewerbspolitik. Kapitel 1 behandelt den Matching-Markt für juristische Referendariatsstellen in Deutschland. Wegen übermäßiger Nachfrage müssen Anwälte oft warten, bevor sie zugewiesen werden. Der aktuell verwendete Algorithmus berücksichtigt nicht die Zeitpräferenzen der Anwälte. Daher werden viele wünschenswerte Eigenschaften nicht erfüllt. Basierend auf dem matching with contracts Modell schlage ich dann einen neuen Mechanismus vor, der die Wartezeit als Vertragsterm verwendet, so dass die Mängel des gegenwärtigen Mechanismus überwunden werden können. In Kapitel 2 analysiere ich den Wettbewerb von zweiseitigen Online-Plattformen, wie sozialen Netzwerken oder Suchmaschinen. Werbetreibende zahlen Geld, um ihre Anzeigen zu platzieren, während Nutzer mit ihren privaten Daten "bezahlen", um Zugang zu der Plattform zu erhalten. Ich zeige, dass das Gleichgewichtsniveau der Datenerhebung verzerrt ist, abhängig von der Intensität des Wettbewerbs und den Targeting-Vorteilen. Weniger Wettbewerb auf jeder Marktseite führt zu mehr Datensammeln. Wenn jedoch Plattformen Geldzahlungen auf beiden Marktseiten verwenden, wird die effiziente Menge an Daten gesammelt. Kapitel 3 untersucht die dynamische Preissetzung auf Märkten für Flug- oder Reisebuchungen, auf denen Wettbewerb während einer endlichen Verkaufszeit mit einer Frist stattfindet. Unter Berücksichtigung der intertemporalen Probleme von Firmen und vorausschauenden Konsumenten hängen die Gleichgewichtspreispfade von der Anzahl der nicht verkauften Kapazitäten und der verbleibenden Verkaufszeit ab. Ich ermittle, dass mehr Voraussicht der Konsumenten die Konsumentenrente erhöht, aber die Effizienz reduziert. Ferner ist Wettbewerbspolitik besonders wertvoll, wenn die Marktkapazitäten zu hoch sind. Des Weiteren kann die ex-ante Produktion von Kapazitäten ineffizient niedrig sein. / This thesis consists of three independent chapters in the fields of matching market design, industrial organization and competition policy. Chapter 1 covers the matching market for lawyer trainee-ship positions in Germany. Because of excess demand lawyers often must wait before being allocated. The currently used algorithm does not take lawyers’ time-preferences into account. Hence, many desirable properties are not satisfied. Then, based on the matching with contacts model, I propose a new mechanism using waiting time as the contractual term, so that the shortcomings of the current mechanism can be overcome. In Chapter 2 I analyze competition of two-sided online platforms, such as social networks or search engines. Advertisers pay money to place their ads, while users “pay” with their private data to gain access to the platform. I show that the equilibrium level of data collection is distorted, depending on the competition intensity and targeting benefits. Less competition on either market side leads to more data collection. However, if platforms use monetary payments on both market sides, data collection would be efficient. Chapter 3 studies dynamic pricing as in markets for airline or travel bookings, where competition takes place throughout a finite selling time with a deadline. Considering the inter-temporal problems of firms and forward-looking consumers, the equilibrium price paths depend on the number of unsold capacities and remaining selling time. I find that more consumer foresight increases consumer surplus yet reduces efficiency. Further, competition policy is especially valuable when market capacities are excessive. Moreover, ex-ante capacity production can be inefficiently low.

Die kumulative Dissertation beschäftigt sich mit stochastischen und deterministischen dynamischen Verkaufsmodellen für langlebige sowie verderbliche Güter. Die analysierten dynamischen Modelle sind durch die Möglichkeit der simultanen Variation von Preis und Werbung in stetiger Zeit charakterisiert und folgen den aktuellen Entwicklungen der Dynamischen Preissetzung. Dabei steht die Berücksichtigung und Analyse von (i) Zeitinhomogenitäten, (ii) Adoptionseffekten, (iii) Oligopolwettbewerb und (iv) der Risikoaversion des Entscheiders im Zentrum der Arbeit. Für die Spezialfälle isoelastischer und exponentieller Nachfrage in Verbindung mit isoelastischer Werbewirkung gelingt es explizite Lösungen der optimalen Preis- und Werbekontrollen herzuleiten. Die optimal gesteuerten Verkaufsprozesse können analytisch beschrieben und ausgewertet werden. Insbesondere werden neben erwarteten Preis- und Restbestandsentwicklungen auch assoziierte Gewinnverteilungen untersucht und Sensitivitätsresultate hergeleitet. Darüber hinaus wird analysiert unter welchen Bedingungen monopolistische Strategien sozial effizient sind und welche Besteuerungs- und Subventionsmechanismen geeignet sind um Effizienz herzustellen. Die Ergebnisse sind in sechs Artikel gefasst und bieten ökonomische Einsichten in verschiedene praktische Verkaufsanwendungen, speziell im Bereich des elektronischen Handels. / The cumulative dissertation deals with stochastic and deterministic dynamic sales models for durable as well as perishable products. The models analyzed are characterized by simultaneous dynamic pricing and advertising controls in continuous time and are in line with recent developments in dynamic pricing. They include the modeling of multi-dimensional decisions and take (i) time dependencies, (ii) adoption effects (iii), competitive settings and (iv) risk aversion, explicitly into account. For special cases with isoelastic demand functions as well as with exponential ones explicit solution formulas of the optimal pricing and advertising feedback controls are derived. Moreover, optimally controlled sales processes are analytically described. In particular, the distribution of profits, the expected evolution of prices as well as inventory levels are analyzed in detail and sensitivity results are obtained. Furthermore, we consider the question whether or not monopolistic policies are socially efficient; in special cases, we propose taxation/subsidy mechanisms to establish efficiency. The results are presented in six articles and provide economic insights into a variety of dynamic sales applications of the business world, especially in the area of e-commerce.

Diese Dissertation analysiert das optimale Zusammenspiel dynamischer Preissetzung, dynamischer Werbung und Bestandsmanagement. Wir betrachten verschiedene Optimierungsprobleme für einen monopolistischen Händler bei gegebener zeitabhängiger deterministischer Nachfrage. In Kapitel 2 erweitern wir das Modell von Rajan et al. (1992). Der Händler darf einen dynamischen Preis, eine dynamische Werberate und die Lagergröße bei fester Verkaufsdauer wählen, so dass der Barwert von Umsatz minus Lager-, Einkaufs- und (nichtlinearen) Werbekosten maximiert wird; zusätzlich zerfällt der Lagerbestand mit exponentieller Rate. Wir ermitteln die optimale Preis-Werbe-Steuerung und die optimale Lagergröße und betrachten auch semi-statische Situationen. Wir führen eine Sensitivitätsanalyse im Hinblick auf den Einfluss der Modellparameter auf die optimalen Ergebnisse durch und vergleichen die Ergebnisse des dynamischen Modells mit denen der semi-statischen Modelle. In Kapitel 3 interpretieren wir den Verkaufsprozess als gesteuerten Diffusionsprozess eines neuen Produktes und die Lagergröße als unerschlossenen Marktanteil. Der Anfangszustand ist exogen gegeben und die Nachfrage hängt zusätzlich vom gegenwärtigen Zustand des Systems ab. Ein Zerfall des Lagerbestandes und alle Kosten bis auf Werbekosten sind ausgenommen. Anders als in Helmes et al. (2013) leiten wir die optimale Steuerung mithilfe des Pontrjaginschen Maximumprinzips her. Als Anwendung betrachten wir das Modell von von Bertalanffy. In Kapitel 4 erweitern wir die Analyse von einperiodigen Modellen auf langfristige Modelle. Die Länge des Verkaufszyklus und die Lagergröße sind Entscheidungsvariablen, wobei die optimalen Steuerungen aus Kapitel 2 bzw. Kapitel 3 während eines Zyklus angewandt werden. Existenzbedingungen für ein optimales Paar aus Zykluslänge und Lagergröße werden hergeleitet. Wir analysieren verschiedene Anwendungs- und Illustrationsbeispiele und verifizieren Strukturaussagen der optimalen Entscheidungsgrößen. / This dissertation analyzes the optimal coordination of dynamic pricing, dynamic advertising, and inventory management. We consider different optimization problems for a monopolistic retailer who faces a time-dependent deterministic demand. In Chapter 2, we generalize the model of Rajan et al. (1992). The retailer is allowed to choose a dynamic price, a dynamic advertising rate, and the inventory capacity for a sales period of fixed length so that the present value of revenue minus inventory, purchasing and (nonlinear) advertising costs is maximized; in addition, the inventory deteriorates at an exponential rate. We derive the optimal dynamic price-advertising control and the optimal capacity and also consider partially static cases. For the optimally controlled dynamic model we carry out a sensitivity analysis with respect to the model parameters and we compare the results of the dynamic model with those of the partially static models. In Chapter 3, we interpret the sales process as the controlled adoption process of a new product and the inventory capacity as untapped market share. The initial state is assumed to be exogenously given and the demand depends on the current state of the system. We exclude, however, deterioration effects and any other costs but the cost of advertising. We derive the optimal controls using a different technique than Helmes et al. (2013) - we apply Pontryagin’s maximum principle. As an interesting application we consider the controlled von Bertalanffy model. In Chapter 4, we extend the analysis of one-period models to multi-period and longterm average models. Assuming that the optimal controls derived in Chapter 2 and Chapter 3 are applied throughout a cycle, we treat the cycle length and the capacity as decision variables. We derive conditions that ensure the existence of an optimal pair of cycle length and capacity. Various examples and illustrations are given, and structural properties of the optimal pair are verified.

Abstract This thesis includes three studies on household preferences for energy goods and services. The first study examines determinants of households’ heating system choices using a choice experiment. The choice sets include six main heating alternatives (district heating, ground heat pump, exhaust air heat pump, solid wood boiler, wood pellet boiler, and electric storage heating) that are described by five attributes (supplementary heating systems, investment costs, operating costs, comfort of use and environmental friendliness). The results imply that hybrid heating appears to be accepted among households. The results also reveal differing preferences for the main heating alternatives and show that they are affected by demographic characteristics. The studied attributes also play a significant role when heating systems are being chosen. The second study is a methodological one that extends the analysis of the first study. The second study explores the effect of perceived choice complexity on the randomness of choices in choice experiments. The study investigates how different self-evaluated factors of choice complexity affect mean scale and scale variance. The findings suggest that perceived choice complexity has a systematic impact on the parameters of econometric models of choice. However, differences exist between alternative self-evaluated complexity-related covariates. The results indicate that individuals who report that answering the choice tasks is more difficult have less deterministic choices. Perceptions of the realism of home heating choice options also affect scale and scale variance. The third study utilizes the choice experiment to analyze households’ willingness to participate in demand side flexibility. The study examines whether individuals are willing to time their electricity usage and heating; whether they are interested in dynamic pricing contracts such as real-time pricing, two-rate tariffs, or power-based tariffs; and how emissions reductions affect their choices. The results indicate that households’ sensitivity to restrictions in electricity usage is much stronger than their sensitivity to restrictions in heating. Households also require compensation to choose real-time pricing over fixed fees. The findings suggest that room may exist for new dynamic electricity distribution contracts, such as power-based tariffs, in the market. Other value-creating elements besides monetary compensation also exist that could incentivize households to offer demand side flexibility because households value power system level reductions in CO2 emissions. / Tiivistelmä Tämä väitöskirja koostuu kolmesta tutkimuksesta, joissa tarkastellaan kotitalouksien preferenssejä energiahyödykkeitä ja -palveluita kohtaan. Ensimmäinen tutkimus keskittyy kotitalouksien lämmitysjärjestelmävalintoihin ja niitä määrittäviin tekijöihin. Tämä tutkimus on tehty valintakoemenetelmällä, jonka valintatilanteet sisältävät kuusi eri päälämmitysjärjestelmävaihtoehtoa (kaukolämpö, maalämpöpumppu, puulämmitys, pellettilämmitys, varaava sähkölämmitys ja poistoilmalämpöpumppu). Päälämmitysjärjestelmiä kuvataan viiden ominaisuuden avulla, jotka ovat tukilämmitysjärjestelmä, investointikustannukset, käyttökustannukset, käyttömukavuus ja ympäristöystävällisyys. Tulosten mukaan kotitalouksien preferenssit päälämmitysjärjestelmävaihtoehtoja kohtaan ovat vaihtelevia. Valintaan vaikuttavat sekä tarkastellut ominaisuudet että kotitalouden demografiset tekijät. Tulokset myös paljastavat, että kotitaloudet suhtautuvat myönteisesti hybridilämmitykseen. Toinen tutkimus on menetelmällinen, missä hyödynnetään ensimmäisen tutkimuksen aineistoa. Tämä tutkimus keskittyy yksilöiden kokeman vastaamisen vaikeuden vaikutuksiin valintakoemenetelmässä. Vastaamisen epätarkkuus tunnistetaan valintakoemenetelmässä skaalan ja skaalavarianssin avulla. Tutkimus tarkastelee, kuinka itsearvioidut vastaamisen vaikeutta mittaavat tekijät vaikuttavat keskimääräiseen skaalaan ja skaalavarianssiin valintojen ekonometrisissa malleissa. Tulosten mukaan koettu vastaamisen vaikeus vaikuttaa systemaattisesti ekonometrisen valintamallin parametreihin. Vastaamisen vaikeutta mittaavien tekijöiden välillä on kuitenkin eroja. Tuloksien perusteella vastaajat, jotka kokevat valintatilanteisiin vastaamisen keskimääräistä vaikeampana, tekevät satunnaisempia valintoja. Myös valintatilanteiden koettu realistisuus vaikuttaa skaalaan ja skaalavarianssiin. Kolmannessa tutkimuksessa arvioidaan kotitalouksien halukkuutta osallistua energian kysyntäjoustoon valintakoemenetelmällä. Tämä tutkimus selvittää ovatko kotitaloudet halukkaitta siirtämään sähkönkulutusta ja lämmitystä, ja kuinka kiinnostuneita he ovat dynaamisista sähkön hinnoittelusopimuksista kuten pörssisähkösopimuksesta, yösähkösopimuksesta tai tehoperusteisesta sopimuksesta. Lisäksi tutkitaan vaikuttavatko järjestelmätason päästövähennykset kotitalouksien valintoihin. Tulosten perusteella kotitaloudet suhtautuvat sähkönkulutuksen rajoituksiin selvästi negatiivisemmin kuin lämmityksen rajoituksiin. Kotitaloudet myös vaativat rahallista korvausta valitakseen pörssisähkösopimuksen kiinteähintaisen sopimuksen sijaan. Tulosten mukaan markkinoilla voisi olla tilaa uudenlaisille sopimustyypeille, kuten tehoperusteiselle vaihtoehdolle. Tulokset osoittavat, että kotitaloudet arvostavat järjestelmätason hiilidioksidipäästövähennyksiä. Täten rahallisen korvauksen lisäksi on olemassa myös muita arvoa luovia tekijöitä lisätä kotitalouksien osallistumista kysyntäjoustoon.

<p>Sequential decision-making is a fundamental class of problem that motivates algorithm designs of online machine learning and reinforcement learning. Arguably, the resulting online algorithms have supported modern online service industries for their data-driven real-time automated decision making. The applications span across different industries, including dynamic pricing (Marketing), recommendation (Advertising), and dosage finding (Clinical Trial). In this dissertation, we contribute fundamental statistical design advances for sequential decision-making algorithms, leaping progress in theory and application of online learning and sequential decision making under uncertainty including online sparse learning, finite-armed bandits, and high-dimensional online decision making. Our work locates at the intersection of decision-making algorithm designs, online statistical machine learning, and operations research, contributing new algorithms, theory, and insights to diverse fields including optimization, statistics, and machine learning.</p> <p><br></p> <p>In part I, we contribute a theoretical framework of continuous risk monitoring for regularized online statistical learning. Such theoretical framework is desirable for modern online service industries on monitoring deployed model's performance of online machine learning task. In the first project (Chapter 1), we develop continuous risk monitoring for the online Lasso procedure and provide an always-valid algorithm for high-dimensional dynamic pricing problems. In the second project (Chapter 2), we develop continuous risk monitoring for online matrix regression and provide new algorithms for rank-constrained online matrix completion problems. Such theoretical advances are due to our elegant interplay between non-asymptotic martingale concentration theory and regularized online statistical machine learning.</p> <p><br></p> <p>In part II, we contribute a bootstrap-based methodology for finite-armed bandit problems, termed Residual Bootstrap exploration. Such a method opens a possibility to design model-agnostic bandit algorithms without problem-adaptive optimism-engineering and instance-specific prior-tuning. In the first project (Chapter 3), we develop residual bootstrap exploration for multi-armed bandit algorithms and shows its easy generalizability to bandit problems with complex or ambiguous reward structure. In the second project (Chapter 4), we develop a theoretical framework for residual bootstrap exploration in linear bandit with fixed action set. Such methodology advances are due to our development of non-asymptotic theory for the bootstrap procedure.</p> <p><br></p> <p>In part III, we contribute application-driven insights on the exploration-exploitation dilemma for high-dimensional online decision-making problems. Such insights help practitioners to implement effective high-dimensional statistics methods to solve online decisionmaking problems. In the first project (Chapter 5), we develop a bandit sampling scheme for online batch high-dimensional decision making, a practical scenario in interactive marketing, and sequential clinical trials. In the second project (Chapter 6), we develop a bandit sampling scheme for federated online high-dimensional decision-making to maintain data decentralization and perform collaborated decisions. These new insights are due to our new bandit sampling design to address application-driven exploration-exploitation trade-offs effectively. </p>

No description available.