Robust Multiclass Queuing Theory for Wait Time Estimation in Resource Allocation Systems

In this paper, we study systems that allocate different types of scarce resources to heterogeneous allocatees based on predetermined priority rules-the U.S. deceased-donor kidney allocation system or the public housing program. We tackle the problem of estimating the wait time of an allocatee who possesses incomplete system information with regard, for example, to his relative priority, other allocatees' preferences, and resource availability. We model such systems as multiclass, multiserver queuing systems that are potentially unstable or in transient regime. We propose a novel robust optimization solution methodology that builds on the assignment problem. For first-come, first-served systems, our approach yields a mixed-integer programming formulation. For the important case where there is a hierarchy in the resource types, we strengthen our formulation through a drastic variable reduction and also propose a highly scalable heuristic, involving only the solution of a convex optimization problem (usually a second-order cone problem).We back the heuristic with an approximation guarantee that becomes tighter for larger problem sizes. We illustrate the generalizability of our approach by studying systems that operate under different priority rules, such as class priority. Numerical studies demonstrate that our approach outperforms simulation. We showcase how our methodology can be applied to assist patients in the U.S. deceased-donor kidney waitlist. We calibrate our model using historical data to estimate patients' wait times based on their kidney quality preferences, blood type, location, and rank in the waitlist

The Price of Fairness

In this paper we study resource allocation problems that involve multiple self-interested parties or players and a central decision maker. We introduce and study the price of fairness, which is the relative system efficiency loss under a “fair” allocation assuming that a fully efficient allocation is one that maximizes the sum of player utilities. We focus on two well-accepted, axiomatically justified notions of fairness, viz., proportional fairness and max-min fairness. For these notions we provide a tight characterization of the price of fairness for a broad family of problems.National Science Foundation (U.S.) (grant DMI- 0556106)National Science Foundation (U.S.) (grant EFRI-0735905

Towards a Pan-European Integrated Groundwater and Surface Water Model: Development and Applications

During the last years, we have developed a model, which is able to simulate hydrological processes at a Pan-European scale. The model has multiple possible uses, including flood forecasting, identification of groundwater recharge / discharge zones and large-scale water resources management. The integrated model is based on the LISFLOOD model, which simulates hydrological processes with a focus on snow and soil hydrology and streamflow routing. The area of interest is the full European continent, divided in 5 × 5 km cells. A conceptual 2D MODFLOW model was linked to improve groundwater simulation. With this coupling, it is now possible to simulate the water exchanges between adjacent cells, and between groundwater and river. Available meteorological data from 1-1-1990 to 31-10-2014 were used as input for the coupled model, together with values of aquifer properties derived from literature. We used observed data of recharge, discharge and hydraulic heads from the Danube river basin to check if the model results correspond to reality. The results show a reasonably high degree of agreement between observed and simulated data, taking into account the limitations of large scale modelling. This model is the first step to improve integrated groundwater and surface water modelling which includes the collection of data and the production of Pan-European groundwater parameter maps

Multi Agent Systems for the Active Management of Electrical Distribution Networks

This Thesis presents an investigation on the technical impacts caused by the steady state operation of Small-Scale Embedded Generators (SSEGs) and also introduces the Small Scale Energy Zone (SSEZ) concept which aims to remove the technical barriers associated with SSEGs through intelligent coordination of large numbers of customerowned SSEGs, energy storage units and controllable loads. This approach represents a move away from the conventional passive, “fit-and-forget” philosophy under which the majority of Low Voltage (LV) distribution networks are currently operated and towards a higher degree of network operational management. The employment of a distributed management and control approach for an SSEZ, realised through the Multi Agent Systems (MAS) technology, is proposed due to the advantages that can potentially be realised in the areas of: (i) scalability and openness, (ii) reliability and resilience and (iii) communications efficiency. A FIPA-compliant MAS-based control approach is designed, developed and evaluated based on the specific SSEZ control requirements. The MAS is composed of three types of agents: direct control agents, indirect control agents and utility agents, exchanging information through the employment of a common ontology. In addition, a relational database management system is also designed and developed in order to be coupled with the developed MAS for data management purposes

Power line network automation over IP

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel UniversityA smart home contains many kinds of devices, sensors and user interfaces. In order for these to communicate with each other and share information and processing power they need to be connected together. Thus, seamless networking and device interconnectivity is a fundamental requirement for a smart home. Unfortunately, this requirement for compliance and compatibility still presents a difficult obstacle as there are numerous competing standards and technologies available today and some devices are completely without communication interface. Current state-of-the-art smart homes are implemented with home based on Web servers in order to surpass the difficulties. Also, a more sophisticated implementation is based on middleware. These two methodologies are expensive to implement. Our proposed system is cost-effective and does not require Web servers or any special hardware and has low complexity. The novelty and the achievement of the thesis is the integration of homogeneous networks through IP. In addition, the system was built-in terms of software and hardware based on a new protocol

Water-Energy-Food-Ecosystems pathways towards reducing water scarcity in Europe

The LISFLOOD-EPIC European setup has now successfully run for the reference 1990-2018 scenario, for single and combined water saving measure scenarios. In this study, five water (policy) saving measures are considered, i.e., efficiency scenarios in irrigation, leakage in the urban water supply, re-using treated wastewater, reducing energy water withdrawals and desalination. This creates a big challenge when it comes to comparisons between the what-if and the reference scenarios because of the complexity of the issue and the lack of a single performance index that can show how much better or worse a scenario is, compared to another. The Water Exploitation Index Plus (WEI+) indicator is used to estimate the impact of water saving measures on water scarcity. It is calculated for the consumption of water and is defined as the ratio of the total water net consumption divided by the available freshwater resources in a region including upstream inflowing water. The differences in WEI+ between a reference scenario and the proposed measure or measures, is a clear indication of the improvement this measure is capable of achieving as a percentage of the total water availability. Therefore, in this report, the results focus on the differences in WEI+ values, rather than on absolute values. The results showed that the scenarios with combined measures are the most effective, and future work will focus to estimate if this improvement will be sufficient to tackle water scarcity issues if climate change is also taken into account.JRC.D.2 - Ocean and Wate

Is Operating Flexibility Harmful Under Debt?

We study the inefficiencies stemming from a firm’s operating flexibility under debt. We find that flexibility in replenishing or liquidating inventory, by providing risk-shifting incentives, could lead to borrowing costs that erase more than one-third of the firm’s value. In this context, we examine the effectiveness of practical and widely used covenants in restoring firm value by limiting such risk-shifting behavior. We find that simple financial covenants can fully restore value for a firm that possesses a midseason inventory liquidation option. In the presence of added flexibility in replenishing or partially liquidating inventory, financial covenants fail, but simple borrowing base covenants successfully restore firm value. Explicitly characterizing optimal covenant tightness for all these cases, we find that better market conditions, such as lower inventory depreciation rate, higher gross margins, or increased product demand, are typically associated with tighter covenants. Our results suggest that inventory-heavy firms can reap the full benefits of additional operating flexibility, irrespective of their leverage, by entering simple debt contracts of the type commonly employed in practice. For such contracts to be effective, however, firms with enhanced flexibility and/or operating in better markets must also be willing to abide by more and/or tighter covenants

Fairness in operations.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 131-136).This thesis deals with two basic issues in resource allocation problems. The first issue pertains to how one approaches the problem of designing the "right" objective for a given resource allocation problem. The notion of what is "right" can be fairly nebulous; we consider two issues that we see as key: efficiency and fairness. We approach the problem of designing objectives that account for the natural tension between efficiency and fairness in the context of a framework that captures a number of problems of interest to operations managers. We state a precise version of the design problem, provide a quantitative understanding of the tradeoff between efficiency and fairness inherent to this design problem and demonstrate the approach in a case study that considers air traffic management. Secondly, we deal with the issue of designing implementable policies that serve such objectives, balancing efficiency and fairness in practice. We do so specifically in the context of organ allocation for transplantation. In particular, we propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the U.S., that are policies based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select his desired criteria and fairness constraints from a broad class of allowable constraints. The method then designs a point system that is based on the selected priority criteria, and approximately maximizes medical efficiency, i.e., life year gains from transplant, while simultaneously enforcing selected fairness constraints. Using our method, we design a point system that has the same form, uses the same criteria and satisfies the same fairness constraints as the point system that was recently proposed by U.S. policymakers. In addition, the point system we design delivers an 8% increase in extra life year gains. We evaluate the performance of all policies under consideration using the same statistical and simulation tools and data as the U.S. policymakers use. We perform a sensitivity analysis which demonstrates that the increase in extra life year gains by relaxing certain fairness constraints can be as high as 30%.by Nikolaos K. Trichakis.Ph.D

On the learning benefits of resource flexibility

Resource flexibility, arguably among the most celebrated operational concepts, is known to provide firms facing demand uncertainty with such benefits as risk pooling, revenue-maximization optionality, and operational hedging. In this paper, we uncover a heretofore unknown benefit: we establish that resource flexibility facilitates learning the demand when the latter is censored, which could, in turn, enable firms to make better-informed future operational decisions, thereby increasing profitability. Further, we quantify these learning benefits of flexibility and find that they could be of the same order of magnitude as the extensively studied risk-pooling benefits of flexibility. This suggests that flexibility’s learning benefits could be a first-order consideration and that extant theories, which view flexibility only as the ability to act ex post, could be underestimating its true value when learning the demand is desirable, for example, when it enables managers to make better ex ante capacity, assortment, or pricing decisions in future periods