A review of network location theory and models

Cataloged from PDF version of article.In this study, we review the existing literature on network location problems. The study has a broad scope that includes problems featuring desirable and undesirable facilities, point facilities and extensive facilities, monopolistic and competitive markets, and single or multiple objectives. Deterministic and stochastic models as well as robust models are covered. Demand data aggregation is also discussed. More than 500 papers in this area are reviewed and critical issues, research directions, and problem extensions are emphasized.Erdoğan, Damla SelinM.S

Optimization Approaches To Protect Transportation Infrastructure Against Strategic and Random Disruptions

Past and recent events have proved that critical infrastructure are vulnerable to natural catastrophes, unintentional accidents and terrorist attacks. Protecting these systems is critical to avoid loss of life and to guard against economical upheaval. A systematic approach to plan security investments is paramount to guarantee that limited protection resources are utilized in the most effcient manner. This thesis provides a detailed review of the optimization models that have been introduced in the past to identify vulnerabilities and protection plans for critical infrastructure. The main objective of this thesis is to study new and more realistic models to protect transportation infrastructure such as railway and road systems against man made and natural disruptions. Solution algorithms are devised to effciently solve the complex formulations proposed. Finally, several illustrative case studies are analysed to demonstrate how solving these models can be used to support effcient protection decisions

Information-theoretic Reasoning in Distributed and Autonomous Systems

The increasing prevalence of distributed and autonomous systems is transforming decision making in industries as diverse as agriculture, environmental monitoring, and healthcare. Despite significant efforts, challenges remain in robustly planning under uncertainty. In this thesis, we present a number of information-theoretic decision rules for improving the analysis and control of complex adaptive systems. We begin with the problem of quantifying the data storage (memory) and transfer (communication) within information processing systems. We develop an information-theoretic framework to study nonlinear interactions within cooperative and adversarial scenarios, solely from observations of each agent's dynamics. This framework is applied to simulations of robotic soccer games, where the measures reveal insights into team performance, including correlations of the information dynamics to the scoreline. We then study the communication between processes with latent nonlinear dynamics that are observed only through a filter. By using methods from differential topology, we show that the information-theoretic measures commonly used to infer communication in observed systems can also be used in certain partially observed systems. For robotic environmental monitoring, the quality of data depends on the placement of sensors. These locations can be improved by either better estimating the quality of future viewpoints or by a team of robots operating concurrently. By robustly handling the uncertainty of sensor model measurements, we are able to present the first end-to-end robotic system for autonomously tracking small dynamic animals, with a performance comparable to human trackers. We then solve the issue of coordinating multi-robot systems through distributed optimisation techniques. These allow us to develop non-myopic robot trajectories for these tasks and, importantly, show that these algorithms provide guarantees for convergence rates to the optimal payoff sequence

Power system planning methods and experiences in the energy transition framework

In recent years, the unbundling of the electricity market together with the profound “energy landscape” transformation have made the transmission network development planning a very complex multi-objective problem. The climate and energy objectives defined at the European level aim for a deepening integration of the European power markets and the electricity sector is recognized as one of the main contributors to the energy transition from a thermal-based power system to a renewable-based one. In the deregulated framework, network planners have to satisfy multiple different objectives, including: facilitating competition between market participants, providing non-discriminatory access to all generation resources for all customers, including green resources, mitigating transmission congestions, efficiently allocating the network development actions, minimizing risks associated with investments, enhancing power system security and reliability and minimizing the transmission infrastructure environmental impact. Further complexities are related to the significant uncertainty about future energy scenarios and policy rules. In particular, the increasing distributed renewable energy source integration dictated by the European energy targets, raises several issues in terms of future power flow patterns, power system flexibility and inertia requirements, and cost-effective development strategies identification. The thesis aims to investigate various aspects concerning the transmission network planning, with particular reference to the Italian power system and the experience gained working in the “Grid Planning and Interconnections Department” of Terna, the Italian Transmission System Operator. One of the main topics of this work is the use of the series compensation to exploit operating limits of underused portions of the HV – EHV transmission network in parallel to critically loaded ones, in order to control and provide alternative paths for power flows. The purpose is to extend the allowable transmission capacity across internal market sections. To this aim, a specific application of series compensation (together with reconductoring) to exploit the transfer capacity of a 250 km long, 230 kV-50 Hz transmission backbone spanning the critical section Centre South – Centre North is illustrated. The results are validated by means of static assessment and similar applications could be hypothesized for grid portions in the South of Italy where the primary network is mainly unloaded whereas the sub-transmission network reaches high levels of loading because of the huge renewable generation capacity situated there. A further characteristic of modern power systems is the need to integrate high levels of renewable energies while fulfilling reliability and security requirements. The offshore wind farms perspectives in the Italian transmission system are evaluated, considering policies, environmental and technical aspects. Furthermore, the adoption of the HVDC technology in parallel to the AC traditional system topic is addressed: planning static and dynamic studies involving a real HVDC Italian project are proposed. In particular, the impact of the planned HVDC link on the loadability and the dynamic performance of the system is investigated in medium and in long-term future planning scenarios. The evaluation of the thermal performance of a specific grid portion in the South of Italy affected by significant increase of power generation by variable energy sources is proposed both in the current situation and in the future scenarios in order to highlight the benefits related to the presence of the planned network reinforcements. Finally, some issues of the prospective reduced inertia systems are illustrated and a possible methodology to evaluate the economic impact of inertia constraints in long-term market studies is proposed. In the light of the emerging concept of power system flexibility, traditional planning evolved to assess the ability of the system to employ its resources when dealing with the changes in load demand and variable generation. Flexibility analyses of the Italian power system, carried out in terms of some market studies-based metrics and grid infrastructure-based indexes, are provided. The flexibility requirements assessment in planning scenarios are of interest to evaluate the impact of network development actions and have been included in the yearly National Development Plan. The last research topic involves the cost-effective target capacity assessment methodology developed by Terna in compliance with the Regulator directives presented together with the results yielded by its application to each significant market section of the Italian power system. The methodology has been positively evaluated from academic independent expert reviewers, and its outputs are relevant for the policy makers, regulatory authority and market participant to assess and co-design the energy transition plan of a future European interconnected power system

Optimization Models Using Fuzzy Sets and Possibility Theory

Optimization is of central concern to a number of disciplines. Operations Research and Decision Theory are often considered to be identical with optimization. But also in other areas such as engineering design, regional policy, logistics and many others, the search for optimal solutions is one of the prime goals. The methods and models which have been used over the last decades in these areas have primarily been "hard" or "crisp", i.e. the solutions were considered to be either feasible or unfeasible, either above a certain aspiration level or below. This dichotomous structure of methods very often forced the modeler to approximate real problem situations of the more-or-less type by yes-or-no-type models, the solutions of which might turn out not to be the solutions to the real problems. This is particularly true if the problem under consideration includes vaguely defined relationships, human evaluations, uncertainty due to inconsistent or incomplete evidence, if natural language has to be modeled or if state variables can only be described approximately. Until recently, everything which was not known with certainty, i.e. which was not known to be either true or false or which was not known to either happen with certainty or to be impossible to occur, was modeled by means of probabilities. This holds in particular for uncertainties concerning the occurrence of events. probability theory was used irrespective of whether its axioms (such as, for instance, the law of large numbers) were satisfied or not, or whether the "events" could really be described unequivocally and crisply. In the meantime one has become aware of the fact that uncertainties concerning the occurrence as well as concerning the description of events ought to be modeled in a much more differentiated way. New concepts and theories have been developed to do this: the theory of evidence, possibility theory, the theory of fuzzy sets have been advanced to a stage of remarkable maturity and have already been applied successfully in numerous cases and in many areas. Unluckily, the progress in these areas has been so fast in the last years that it has not been documented in a way which makes these results easily accessible and understandable for newcomers to these areas: text-books have not been able to keep up with the speed of new developments; edited volumes have been published which are very useful for specialists in these areas, but which are of very little use to nonspecialists because they assume too much of a background in fuzzy set theory. To a certain degree the same is true for the existing professional journals in the area of fuzzy set theory. Altogether this volume is a very important and appreciable contribution to the literature on fuzzy set theory

Robust network design under polyhedral traffic uncertainty

Ankara : The Department of Industrial Engineering and The Institute of Engineering and Science of Bilkent Univ., 2007.Thesis (Ph.D.) -- Bilkent University, 2007.Includes bibliographical references leaves 160-166.In this thesis, we study the design of networks robust to changes in demand estimates. We consider the case where the set of feasible demands is defined by an arbitrary polyhedron. Our motivation is to determine link capacity or routing configurations, which remain feasible for any realization in the corresponding demand polyhedron. We consider three well-known problems under polyhedral demand uncertainty all of which are posed as semi-infinite mixed integer programming problems. We develop explicit, compact formulations for all three problems as well as alternative formulations and exact solution methods. The first problem arises in the Virtual Private Network (VPN) design field. We present compact linear mixed-integer programming formulations for the problem with the classical hose traffic model and for a new, less conservative, robust variant relying on accessible traffic statistics. Although we can solve these formulations for medium-to-large instances in reasonable times using off-the-shelf MIP solvers, we develop a combined branch-and-price and cutting plane algorithm to handle larger instances. We also provide an extensive discussion of our numerical results. Next, we study the Open Shortest Path First (OSPF) routing enhanced with traffic engineering tools under general demand uncertainty with the motivation to discuss if OSPF could be made comparable to the general unconstrained routing (MPLS) when it is provided with a less restrictive operating environment. To the best of our knowledge, these two routing mechanisms are compared for the first time under such a general setting. We provide compact formulations for both routing types and show that MPLS routing for polyhedral demands can be computed in polynomial time. Moreover, we present a specialized branchand-price algorithm strengthened with the inclusion of cuts as an exact solution tool. Subsequently, we compare the new and more flexible OSPF routing with MPLS as well as the traditional OSPF on several network instances. We observe that the management tools we use in OSPF make it significantly better than the generic OSPF. Moreover, we show that OSPF performance can get closer to that of MPLS in some cases. Finally, we consider the Network Loading Problem (NLP) under a polyhedral uncertainty description of traffic demands. After giving a compact multicommodity formulation of the problem, we prove an unexpected decomposition property obtained from projecting out the flow variables, considerably simplifying the resulting polyhedral analysis and computations by doing away with metric inequalities, an attendant feature of most successful algorithms on NLP. Under the hose model of feasible demands, we study the polyhedral aspects of NLP, used as the basis of an efficient branch-and-cut algorithm supported by a simple heuristic for generating upper bounds. We provide the results of extensive computational experiments on well-known network design instances.Altın, AyşegülPh.D

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