Emergency response network design for hazardous materials transportation with uncertain demand

Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats), such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method

Using Laboratory Experiments to Design Efficient Market Institutions: The case of wholesale electricity markets

This paper assesses the contribution of laboratory experiments to the economics of design applied to the electricity industry. The analysis is dedicated to wholesale markets, and reviews the results accumulated to date concerning both the general architecture of power markets and the very details of the market rules or institution, that is the auction rule. We argue that these experimental results contribute to a better understanding of the performances properties and implementation features of competitive market designs and that experimental economics has proven very useful to public authorities to inform the restructuring of electricity industry. It thus confirms the role of experimental economics as a complement to theoretical approaches in the design effort.Experimental economics; market design; design economics; electricity auction;

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

Proactive-reactive, robust scheduling and capacity planning of deconstruction projects under uncertainty

A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution

Strategic network planning in biomass-based supply chains

Fossil resources are limited and will run short. Moreover, the extensive usage of fossil resources is discussed as a key driver for climate change which means that a changeover in basic economic and ecological thinking is necessary. Especially for energy production, there has to be a movement away from the usage of fossil resources and towards renewable resources like wind, water, sun, or biomass. Within the first part of this work a structured review of recent literature on the long-term, strategic planning of biomass-based supply chains is provided. Therefore, in the first step, the overall research field bioeconomy by means of the various utilization pathways of biomass is structured and the demand-oriented view of supply chain management models and the supply-oriented view of bioeconomy are combined. In the second step, a literature review of operations research models and methods for strategic supply chain planning in biomass-based industries are provided. Thirdly, trends are identified and conclusions about research gaps are drawn. One of the identified research gaps is to make biomass-based supply chains profitable on their own, i.e., without governmental subsidies. Therefore, new optimization models are necessary, which should be as close to reality as possible, by for example considering risks and actual surrounding constraints concerning the legal framework. Within the second part of this work, an approach for strategic optimization of biogas plants considering increased flexibility is developed. Biogas plants can produce their energy flexibly and on-demand if their design is adjusted adequately. In order to achieve a flexibly schedulable biogas plant, the design of this plant has to be adapted to decouple the biogas and electricity production. Therefore, biogas storage possibilities and additional electrical capacity are necessary. The investment decision about the size of the biogas storage and the additional electrical capacity depends on the fluctuation of energy market prices and the availability of governmental subsidies. This work presents an approach supporting investment decisions to increase the flexibility of a biogas plant by installing gas storages and additional electrical capacities under consideration of revenues out of direct marketing at the day-ahead market. In order to support the strategic, long-term investment decisions, an operative plant schedule for the future, considering different plant designs given as investment strategies, using a mixed-integer linear programming (MILP) model in an uncertain environment is optimized. The different designs can be evaluated by calculating the net present value (NPV). Moreover, an analysis concerning current dynamics and uncertainties within spot market prices is executed. Furthermore, the influences concerning the variation of spot market prices compared to the influence of governmental subsidies, in particular, the flexibility premium, are revealed by computational results. Besides, the robustness of the determined solution is analyzed concerning uncertainties. The focus of the third part of the work is to consider variable substrate feeding in the mentioned optimization approach because it is expected that variable substrate feeding and thus a demand-oriented biogas production can influence the optimized plant design. In order to support this extension, an operative plant schedule for the future, considering (non-) linear technical characteristics of the biogas plant and the legal framework is optimized. Therefore, mixed-integer linear programming models with integrated approximation approaches of non-linear parts, representing the biogas production rates, are constructed. Furthermore, the influences of fluctuating spot market prices, governmental subsidies, and biomass feedstock prices on the decisions are analyzed for a fictional case example, which is based on a biogas plant in southern Germany. These numerical experiments show that variable substrate feeding can play a decisive role during the optimization of a biogas plant schedule as part of a long-term design optimization. However, the size of the strategic optimization problem makes the use of a heuristic solution algorithm necessary.Fossile Ressourcen sind begrenzt und werden zur Neige gehen. Darüber hinaus wird über die extensive Nutzung fossiler Ressourcen als wesentlicher Treiber des Klimawandels diskutiert, so dass ein Umdenken in der ökonomischen und ökologischen Grundhaltung notwendig ist. Insbesondere bei der Energieerzeugung muss eine Abkehr von der Nutzung fossiler Ressourcen und eine Ausrichtung auf erneuerbare Ressourcen wie Wind, Wasser, Sonne oder Biomasse erfolgen. Im ersten Teil dieser Arbeit wird ein strukturierter Überblick über die aktuelle Fachliteratur zur langfristigen, strategischen Planung von biomassebasierten Supply Chains gegeben. Dazu wird in einem ersten Schritt das gesamte Forschungsfeld "Bioökonomie" anhand der verschiedenen Nutzungspfade von Biomasse strukturiert und die nachfrageorientierte Sichtweise von Supply Chain Management Modellen und die angebotsorientierte Sichtweise der Bioökonomie zusammengeführt. Im zweiten Schritt wird ein Literaturüberblick über Operations-Research-Modelle und Methoden zur strategischen Supply-Chain-Planung in biomassebasierten Branchen gegeben. Im dritten Schritt werden Trends identifiziert und Schlussfolgerungen über Forschungslücken gezogen. Eine der identifizierten Forschungslücken besteht darin, biomassebasierte Supply Chains selbständig, d.h. ohne staatliche Subventionen, profitabel zu machen. Hierfür sind neue Optimierungsmodelle notwendig, die möglichst realitätsnah sein sollten, indem sie z.B. Risiken und tatsächliche Rahmenbedingungen bezüglich der rechtlichen Vorgaben berücksichtigen. Im zweiten Teil dieser Arbeit wird ein Ansatz zur strategischen Optimierung von Biogasanlagen unter Berücksichtigung einer Flexibilitätserhöhung entwickelt. Biogasanlagen können bei geeigneter Auslegung ihre Energie flexibel und bedarfsgerecht produzieren. Um eine Biogasanlage flexibel planbar zu betreiben, muss das Design dieser Anlage so angepasst werden, dass die Biogas- und Stromproduktion entkoppelt werden. Dazu sind Biogasspeichermöglichkeiten und zusätzliche elektrische Kapazität notwendig. Die Investitionsentscheidung über die Größe des Biogasspeichers und der zusätzlichen elektrischen Kapazität hängt von der Schwankung der Energiemarktpreise und der Verfügbarkeit staatlicher Fördermittel ab. Diese Arbeit stellt einen Ansatz zur Unterstützung von Investitionsentscheidungen zur Erhöhung der Flexibilität einer Biogasanlage durch die Installation von Gasspeichern und zusätzlichen elektrischen Kapazitäten unter Berücksichtigung von Erlösen aus der Direktvermarktung am Day-Ahead-Markt vor. Um die strategischen, langfristigen Investitionsentscheidungen zu unterstützen, wird ein operativer Anlagenfahrplan für die Zukunft unter Berücksichtigung verschiedener Anlagendesigns, die als Investitionsstrategien vorgegeben sind, mit Hilfe eines gemischt-ganzzahligen linearen Optimierungsmodells (MILP), unter Berücksichtigung von Unsicherheit, optimiert. Die verschiedenen Designs können durch die Berechnung des Kapitalwerts (NPV) bewertet werden. Darüber hinaus wird eine Analyse der aktuellen Dynamik und der Unsicherheiten der Spotmarktpreise durchgeführt. Darüber hinaus werden die Einflüsse der Varianz der Spotmarktpreise im Vergleich zum Einfluss staatlicher Subventionen, insbesondere der Flexibilitätsprämie, durch Berechnungsergebnisse aufgezeigt. Außerdem wird die Robustheit der ermittelten Lösung hinsichtlich der Unsicherheiten analysiert. Der Fokus des dritten Teils der Arbeit liegt auf der Berücksichtigung eines variablen Substratmanagements in dem entwickelten Optimierungsansatz, da erwartet wird, dass eine variable Substrateinspeisung und damit eine bedarfsgerechte Biogasproduktion das optimierte Anlagendesign beeinflussen kann. Um diese Erweiterung umzusetzen, wird ein operativer Anlagenfahrplan für die Zukunft unter Berücksichtigung (nicht-) linearer technischer Eigenschaften der Biogasanlage und der gesetzlichen Rahmenbedingungen optimiert. Dazu werden gemischt-ganzzahlige lineare Optimierungsmodelle mit integrierten Approximationsansätzen der nichtlinearen Anteile, welche die Biogasproduktionsraten repräsentieren, konstruiert. Des Weiteren werden die Einflüsse von schwankenden Spotmarktpreisen, staatlichen Förderungen und Biomasse-Rohstoffpreisen auf die Entscheidungen für ein fiktives Fallbeispiel, das auf einer Biogasanlage aus Süddeutschland basiert, analysiert. Die numerischen Experimente zeigen, dass die variable Substrateinspeisung bei der Optimierung des Fahrplans einer Biogasanlage im Rahmen einer langfristigen Anlagenoptimierung eine entscheidende Rolle spielen kann. Die Größe des strategischen Optimierungsproblems macht jedoch den Einsatz eines heuristischen Lösungsalgorithmus notwendig

Pricing irrigation water : a literature survey

As water scarcity and population pressures increase, more countries are adopting water pricing mechanisms, as their primary means of regulating the consumption of irrigation water. The way to allocate water efficiently is to"get the prices right", but how to accomplish this is open to debate. Water pricing methods are sensitive to the social, physical, institutional, and political setting. To assess the costs and benefits of a particular irrigation project, the pricing method must be tailored to local circumstances. The author's survey of the resource economics literature on irrigation services and pricing, will be useful for developing comprehensive guidelines for water policy practitioners. He synthesizes accumulated knowledge about the implementation, and performance of various water pricing methods used over the past two decades: volumetric pricing (marginal cost pricing), output and input pricing, per area pricing, tiered pricing, two part tariffs, and water markets. As water scarcity and population pressures increase, more countries are adopting water pricing mechanisms as their primary means of regulating the consumption of irrigation water. The way to allocate water efficiently is to"get the prices right", but how to accomplish this is open to debate. Water pricing methods are sensitive to the social, physical, institutional, and political setting. To assess the costs and benefits of a particular irrigation project, the pricing method must be tailored to local circumstances. The author's survey of the resource economics literature on irrigation services and pricing, will be useful for developing comprehensive guidelines for water policy practitioners. He synthesizes accumulated knowledge about the implementation, and performance of various water pricing methods used over the past two decades: volumetric pricing (marginal cost pricing), output and input pricing, per area pricing, tiered pricing, two part tariffs, and water markets.Water and Industry,Water Conservation,Water Resources Law,Environmental Economics&Policies,Sanitation and Sewerage,Water and Industry,Water Conservation,Water Use,Water Supply and Sanitation Governance and Institutions,Town Water Supply and Sanitation

Proactive-reactive, robust scheduling and capacity planning of deconstruction projects under uncertainty

A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution

Multicriteria methodologies for the appraisal of smart grid projects when flexibility competes with grid expansion

The severe consequences expected due to the increased frequency and intensity of extreme weather events call for improving the environmental sustainability of our society. The electricity sector is pivotal in the path toward a climate-neutral society. Nowadays, the massive use of renewable energy sources requires that electricity demand follows energy production. Demand has to be flexible, as well as the renewable generation and the grid infrastructures. The power system has to assume a decentralised structure and integrate the transportation and cooling and heating sectors. All customers connected to the electrical grid have to contribute to the power system management and participate in the related markets. The power system has to become smart; all technical and market processes have to be digitalised to enable new functionalities and services. The power system transformation requires rethinking planning and operation practices to accommodate the changes and take advantage of the related opportunities. The novel features and services available in the active and flexible power system will influence the customers' daily habits; therefore, the impacts generated by planning initiatives will cross the power system borders by impacting society as a whole. Since the power system will be operated closer to its technical limits, it is crucial to enhance the management of uncertainties by the increased accuracy of load and generation forecast. This thesis addresses the ongoing power system transformation by focusing on the distribution system, which will face unprecedented changes. This thesis concerns novel approaches for appraising the project initiatives based on the use of the users' flexibility connected to the grid. Traditional appraisal tools are no longer effective; therefore, decision-makers have to be supported with tools capable of capturing the complexity of the future power system in which flexibility measures compete with grid expansion. In this thesis, an assessment framework for smart grid initiatives which combines the cost-benefit analysis and the multi-criteria analysis proposed. Based on international guidelines, this framework allows for a systematic and simultaneous assessment of tangible and the intangible impacts considering conflicting criteria. To complete the assessment framework, a novel methodology which combines Regret Theory and multi-criteria analysis is proposed. The proposed methodology represents one of the main contributions of this dissertation. It supports the decision-maker to identify the most valuable option by decomposing the complex decision-making problem of smart grid planning and rejecting personal biases by avoiding the need for defining the evaluation criteria relevance. However, the stakeholders’ perspective can be included in terms of constraints for the minimax optimisation problem. In conclusion, the contribution of the thesis is to provide decision-making support tools for strategical power system planning. The research activities described in this document have been aimed at supporting system operators and regulatory bodies by providing tools for smart grid project appraisal and improving the accuracy of power system studies considering the novel context features

A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

Decision support system for a reactive management of disaster-caused supply chain disturbances

This research contribution presents the Reactive Disaster and supply chain Risk decision Support System ReDRiSS which supports decision-makers of logistical disaster management in the immediate aftermath of a supply chain disturbance. ReDRiSS suggests a methodology which combines approaches from scenario techniques, operations research and decision theory. Two case studies are provided which focus on decision situations of humanitarian logistics and of business continuity management