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Equitable optimization of US airline route networks

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 2023年第1期102卷

作者： Eskenazi, Andy G. Joshi, Arnav P. Butler, Landon G. Ryerson, Megan S. Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19104 USA Univ Penn Dept Math Philadelphia PA USA Univ Penn Dept Elect & Syst Engn Philadelphia PA USA Univ Penn Dept City & Reg Planning Philadelphia PA USA

Restructuring route networks (i.e., modifying the graph of origin-destination pairs) remains a promising alternative for reducing the airline industry's environmental impact. However, there exists a fundamental trade-off between emissions from flight and airport accessibility, since flights connecting underserved, low-accessibility communities tend to possess high CO2/seat-mile ratios. Thus, this work develops an open-source analytical framework and methodology that restructures U.S. airline route networks to simultaneously minimize emissions and maximize airport accessibility. To achieve this goal, this paper designs a metric to quantify airport accessibility and combines it with an open-source system-wide emissions estimation methodology. This facilitates the creation of a mixed-integer linear optimization model that returns revised flight frequencies and aircraft allotment. Using United Airlines 2019 Q3 data as a case study, this model is able to construct an alternative route network with a 25% reduction on the total number of flights, 4.4% decrease in the average emissions per seatmile and a 17.6% improvement in the spread of the airports' accessibility scores, all while satisfying historic passenger demand.

关键词： Airport accessibility Flight emissions mixed-integer linear optimization Airline network planning

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A decision-making framework for the optimal design of renewable energy systems under energy-water-land nexus considerations

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SCIENCE OF THE TOTAL ENVIRONMENT 2022年 827卷 154185-154185页

作者： Cook, Julie Di Martino, Marcello Allen, R. Cory Pistikopoulos, Efstratios N. Avraamidou, Styliani Texas A&M Univ Artie McFerrin Dept Chem Engn Jack E Brown Chem Engn Bldg3122 TAMU College Stn TX 77843 USA Texas A&M Univ Texas A&M Energy Inst 1617 Res Pkwy College Stn TX 77843 USA Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA

The optimal allocation of land for energy generation is of emergent concern due to an increasing demand for renewable power capacity, land scarcity, and the diminishing supply of water. Therefore, economically, socially and environmentally optimal design of new energy infrastructure systems require the holistic consideration of water, food and land resources. Despite huge efforts on the modeling and optimization of renewable energy systems, studies navigating the multi-faceted and interconnected food-energy-water-land nexus space, identifying opportunities for beneficial improvement, and systematically exploring interactions and trade-offs are still limited. In this work we present the foundations of a systems engineering decision-making framework for the trade-off analysis and optimization of water and land stressed renewable energy systems. The developed framework combines mathematical modeling, optimization, and data analytics to capture the interdependencies of the nexus elements and therefore facilitate informed decision making. The proposed framework has been adopted for a water-stressed region in south-central 'texas. The optimal solutions of this case study highlight the significance of geographic factors and resource availability on the transition towards renewable energy generation.

关键词： Renewable energy Energy storage Multi-scale optimization mixed-integer linear optimization Energy systems engineering

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Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

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APPLIED ENERGY 2021年 292卷 116880-116880页

作者： van Beuzekom, Iris Hodge, Bri-Mathias Slootweg, Han Eindhoven Univ Technol Elect Energy Syst Grp Flux 2-133POB 513 NL-5600 MB Eindhoven Netherlands Natl Renewable Energy Lab Power Syst Engn Ctr 15013 Denver W Pkwy Golden CO 80401 USA Univ Colorado Dept Elect Comp & Energy Engn Renewable & Sustainable Energy Inst 425 UCBECOT 342 Boulder CO 80309 USA Enexis Netbeheer Asset Management Magistratenlaan 116 NL-5223 MB Shertogenbosch Netherlands ORTEC Houtsingel 5POB 75 NL-2719 EA Zoetermeer Netherlands

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers;building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO2-emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

关键词： mixed-integer linear optimization Investment planning Integrated energy systems Climate policy Facility location network design

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Continuous-time planning and scheduling of internal closed-loop systems in multi-stage supply chain networks with recycling trade-offs

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SUSTAINABLE FUTURES 2022年 4卷

作者： Albrecht, Wolfgang Univ Greifswald Fac Law & Econ Friedrich Loeffler Str 70 D-17489 Greifswald Germany

The article considers supply chain networks of process industries within several days or months. Continuous-time production, distribution, and recycling of goods and their subsequent reintegration into closed loops is analyzed. The aim of the study is to quantify trade-offs resulting from decisions on the usage of recyclable quantities. A mixed-integer linear programming model based on a new network structure with third-party contractors is developed. A numerical study consists of thirty scenarios with randomly generated data. The model allows for generating compromise solutions in acceptable computation times, if limiting the transfer of recyclable goods to disposal results in decreasing network profits.

关键词： Supply chain management Short-term planning horizon Continuous-time scheduling Recycling Closed-loop networks mixed-integer linear optimization

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Voltage balance for five-level DCC based on mixed-integer linear programming

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 124卷 106302-106302页

作者： Montero-Robina, Pablo Gordillo, Francisco Gomez-Estern, Fabio Salas, Francisco Univ Seville Escuela Tecn Super Ingn Seville Spain Univ Loyola Andalucia Escuela Tecn Super Ingn Seville Spain

In power converters, the modulation stage commands the switching devices to drive the converter outputs to the voltage required by the inner controllers in order to achieve their objectives. However, in multilevel converters, the modulation may be in charge of an additional goal since it also has to tackle with the capacitor voltage balancing issue. This paper formulates the modulation of multilevel three-phase power converters, specifically five-level diode-clamped converters (DCC), as a mixed-integer linear optimization problem. In this paper, it is shown that the presented optimization problem can deal with the capacitor voltage balance at the same time that the number of commutations is minimized. The problem is solved offline and its solution is stored in a lookup table to be used during normal operation. Then, an online procedure to obtain the levels that modulate each phase from the lookup table is given. Comparisons with model predictive control, space-vector-based algorithms and other modulation approaches are presented in simulations. Several experimental results are presented showing the feasibility of this approach with changes in the operating conditions.

关键词： Multilevel converter Diode-clamped converter mixed-integer linear optimization Capacitor voltage balance Five-level converter Modulation and control of power converters

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Algorithms for Optimal Power Flow in Isolated Distribution Networks Using Different Battery Energy Storage Models

Algorithms for Optimal Power Flow in Isolated Distribution N...

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IEEE-Power-and-Energy-Society Innovative Smart Grid Technologies Conference (ISGT)

作者： Shah, Chinmay Wies, Richard Univ Alaska Fairbanks Elect & Comp Engn Dept Fairbanks AK 99775 USA

ISBN: (纸本)9781728131030

Battery energy storage systems (BESS) are crucial for remote communities operating isolated distribution networks (IDNs) that are transitioning from dependence on diesel generators to renewable energy sources for their energy needs. Since renewable energy sources are variable, these isolated communities still depend on diesel generators during periods when the output of renewable resources are lower than the demand or not available. In order to minimize the dependence on high-cost diesel fuel it is necessary to accurately model the BESS for grid optimization in IDNs. This paper employs existing BESS models, including linear, convex nonlinear, and nonlinear, in a 17 bus test system extracted from the IEEE-123 bus feeder model with the inclusion of network constraints. The optimal power flow problem formulated with each of the three BESS models shows that convex relaxation of the non-convex equation for a non-linear BESS model significantly reduces the computation time with comparable results.

关键词： Convex relaxation energy storage mixed-integer linear optimization nonlinear optimization isolated distribution network optimal power flow

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Robust optimization of Dose-Volume Metrics for Prostate HDR-Brachytherapy Incorporating Target and OAR Volume Delineation Uncertainties

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INFORMS JOURNAL ON COMPUTING 2019年第1期31卷 100-114页

作者： Balvert, Marleen den Hertog, Dick Hoffmann, Aswin L. Tilburg Univ Ctr Econ Res CentER Dept Econometr & Operat Res NL-5000 LE Tilburg Netherlands Ctr Wiskunde Informat NL-1098 XG Amsterdam Netherlands Univ Utrecht Theoret Biol & Bioinformat NL-3508 TC Utrecht Netherlands Helmholtz Zentrum Dresden Rossendorf Inst Radiooncol Dresden Germany Tech Univ Dresden Univ Hosp Carl Gustav Carus Dept Radiotherapy & Radiooncol Dresden Germany Maastricht Univ Med Ctr Dept Radiat Oncol MAASTRO GROW Sch Oncol & Dev Biol Maastricht Netherlands

In radiation therapy planning, uncertainties in the definition of the target volume yield a risk of underdosing the tumor. The traditional corrective action in the context of external beam radiotherapy (EBRT) expands the clinical target volume (CTV) with an isotropic margin to obtain the planning target volume (PTV). However, the EBRT-based PTV concept is not directly applicable to brachytherapy (BT) since it can lead to undesirable dose escalation. Here, we present a treatment plan optimization model that uses worst-case robust optimization to account for delineation uncertainties in interstitial high-dose-rate BT of the prostate. A scenario-based method was developed that handles uncertainties in index sets. Heuristics were included to reduce the calculation times to acceptable proportions. The approach was extended to account for delineation uncertainties of an organ at risk (OAR) as well. The method was applied on data from prostate cancer patients and evaluated in terms of commonly used dosimetric performance criteria for the CTV and relevant OARs. The robust optimization approach was compared against the classical PTV margin concept and against a scenario-based CTV margin approach. The results show that the scenario-based margin and the robust optimization method are capable of reducing the risk of underdosage to the tumor. As expected, the scenario-based CTV margin approach leads to dose escalation within the target, whereas this can be prevented with the robust model. For cases where rectum sparing was a binding restriction, including uncertainties in rectum delineation in the planning model led to a reduced risk of a rectum overdose, and in some cases, to reduced target coverage.

关键词： brachytherapy delineation uncertainties mixed-integer linear optimization robust optimization tratment planning

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Robust optimal discrete arc sizing for tree-shaped potential networks

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COMPUTATIONAL optimization AND APPLICATIONS 2019年第3期73卷 791-819页

作者： Robinius, Martin Schewe, Lars Schmidt, Martin Stolten, Detlef Thuerauf, Johannes Welder, Lara Forschungszentrum Julich Inst Electrochem Proc Engn IEK 3 Wilhelm Johnen Str D-52428 Julich Germany Friedrich Alexander Univ Erlangen Nurnberg FAU Discrete Optimizat Cauerstr 11 D-91058 Erlangen Germany Energie Campus Nurnberg Further Str 250 D-90429 Nurnberg Germany Trier Univ Dept Math Univ Sring 15 D-54296 Trier Germany Rhein Westfal TH Aachen Chair Fuel Cells Forschungszentrum Julich Inst Electrochem Proc Engn IEK 3 Wilhelm Johnen Str D-52428 Julich Germany

We consider the problem of discrete arc sizing for tree-shaped potential networks with respect to infinitely many demand scenarios. This means that the arc sizes need to be feasible for an infinite set of scenarios. The problem can be seen as a strictly robust counterpart of a single-scenario network design problem, which is shown to be NP-complete even on trees. In order to obtain a tractable problem, we introduce a method for generating a finite scenario set such that optimality of a sizing for this finite set implies the sizing's optimality for the originally given infinite set of scenarios. We further prove that the size of the finite scenario set is quadratically bounded above in the number of nodes of the underlying tree and that it can be computed in polynomial time. The resulting problem can then be solved as a standard mixed-integer linear optimization problem. Finally, we show the applicability of our theoretical results by computing globally optimal arc sizes for a realistic hydrogen transport network of Eastern Germany.

关键词： Discrete arc sizing Network design Potential networks Scenario generation Robust optimization mixed-integer linear optimization 90-08 90B10 90C11 90C35 90C90

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Extrapolating curvature lines in rough concept sketches using mixed-integer nonlinear optimization

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optimization AND ENGINEERING 2019年第2期20卷 337-347页

作者： D'Ambrosio, Claudia Lee, Jon Liberti, Leo Ovsjanikov, Maks CNRS LIX Ecole Polytech F-91128 Palaiseau France Univ Michigan Dept IOE Ann Arbor MI 48109 USA

We present several mathematical-optimization formulations for a problem that commonly occurs in geometry processing and specifically in the design of so-called smooth direction fields on surfaces. This problem has direct applications in 3D shape parameterization, texture mapping, and shape design via rough concept sketches, among many others. A key challenge in this setting is to design a set of unit-norm directions, on a given surface, that satisfy some prescribed constraints and vary smoothly. This naturally leads to mixed-integer optimization formulations, because the smoothness needs to be formulated with respect to angle-valued variables, which to compare one needs to fix the discrete jump between nearby points. Previous works have primarily attacked this problem via a greedy ad-hoc strategy with a specialized solver. We demonstrate how the problem can be cast in a standard mathematical-optimization form, and we suggest several relaxations that are especially adapted to modern mathematical-optimization solvers. .

关键词： mixed-integer nonlinear optimization mixed-integer linear optimization Computer graphics Sketching

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Modelling and (re-)planning periodic home social care services with loyalty and non-loyalty features

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2019年第1期277卷 284-299页

作者： Gomes, Maria Isabel Pereira Ramos, Tania Rodrigues Univ Nova Lisboa CMA Fac Sci & Technol P-2829516 Monte De Caparica Caparica Portugal Univ Nova Lisboa Dept Math Fac Sci & Technol P-2829516 Monte De Caparica Caparica Portugal Univ Lisbon Ctr Management Studies Inst Super Tecn CEG IST P-1049001 Lisbon Portugal Inst Univ Lisboa ISCTE IUL Business Res Unit BRU IUL Av Forcas Armadas P-1649026 Lisbon Portugal

The aging population alongside little availability of informal care are two of the several factors leading to an increased need for assisted living support. In this work, we tackle a home social care service problem, motivated by two real case studies where a new loyalty scheme must be considered: within a week, patient-caregiver loyalty should be pursued but, between weeks, the caregivers must rotate among patients (non-loyalty). In addition, a common situation in this kind of service is also addressed: the need of a constant re-planning caused by the leaving of patients and the arrival of new ones. This new plan should be such that minimum disturbance is caused to the visiting hours of current patients, the caregivers' travelling time between visits is minimized, and the workload is balanced among caregivers. A multi-objective optimization approach based on mixed-integer models is developed. Results on the two real case studies show that both institutions can efficiently re-plan their activities without much disturbance on the visits of their patients, and with a patient-caregiver loyalty scheme suiting their needs. (C) 2019 Elsevier B.V. All rights reserved.

关键词： OR in health services Homecare service (Re-)routing and (Re-)scheduling Non-loyalty mixed-integer linear optimization

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