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Comparing Spatial and Scenario Decomposition for Stochastic Hydrothermal Unit Commitment Problems

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2018年第3期9卷 1307-1317页

作者： Scuzziato, Murilo Reolon Finardi, Erlon Cristian Frangioni, Antonio Inst Fed Santa Catarina Dept Acad Electrotecn BR-88020300 Florianopolis SC Brazil Univ Fed Santa Catarina Dept Engn Eletr BR-88040900 Florianopolis SC Brazil Univ Pisa Dipartimento Informat I-56126 Pisa Italy

Solving very-large-scale optimization problems frequently require to decompose them in smaller subproblems, which are iteratively solved to produce useful information. One such approach is the Lagrangian relaxation (LR), a general technique that leads to many different decomposition schemes. The LR produces a lower bound of the objective function and useful information for heuristics aimed at constructing feasible primal solutions. In this paper, we compare the main LR strategies used so far for stochastic hydrothermal unit commitment problems, where uncertainty mainly concerns water availability in reservoirs and demand (weather conditions). The problem is customarily modeled as a two-stage mixed-integer optimization problem. We compare different decomposition strategies (unit and scenario schemes) in terms of quality of produced lower bound and running time. The schemes are assessed with various hydrothermal systems, considering different configuration of power plants, in terms of capacity and number of units.

关键词： Lagrangian relaxation mixed-integer linear programming hydrothermal stochastic unit commitment

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Coordinated platooning with multiple speeds

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2018年 90卷 213-225页

作者： Luo, Fengqiao Larson, Jeffrey Munson, Todd Northwestern Univ Dept Ind Engn & Management Sci Evanston IL 60202 USA Argonne Natl Lab Div Math & Comp Sci Lemont IL 60439 USA

In a platoon, vehicles travel one after another with small intervehicle distances;trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on the time each vehicle is allowed to stay in the network;this time affects vehicles' available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.

关键词： Vehicle platooning routing Optimization modeling mixed-integer linear programming

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Stochastic maximum flow interdiction problems under heterogeneous risk preferences

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COMPUTERS & OPERATIONS RESEARCH 2018年 90卷 97-109页

作者： Lei, Xiao Shen, Siqian Song, Yongjia Univ Int Business & Econ Beijing Peoples R China Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA Virginia Commonwealth Univ Dept Stat Sci & Operat Res Richmond VA USA

We consider a generic maximum flow interdiction problem that involves a leader and a follower who take actions in sequence. Given an interdiction budget, the leader destroys a subset of arcs to minimize the follower's maximum flows from a source to a sink node. The effect from an interdiction action taken on each arc is random, following a given success rate of decreasing the arc's capacity to zero. The follower can add additional arc capacities for mitigating flow losses, after knowing the leader's interdiction plan but before realizing the uncertainty. We consider risk-neutral and risk-averse behaviors of the two players and investigate five bi-level/tri-level programming models for different risk-preference combinations. The models incorporate the expectation, left-tail, and right-tail Conditional Value-at-Risk (CVaR) as commonly used convex risk measures for evaluating random maximum flows in the leader's and follower's objectives. We reformulate each model as an equivalent mixed-integer linear program and test them on real-world network instances to demonstrate interactions between the leader and the follower under various risk-preference settings. (c) 2017 Elsevier Ltd. All rights reserved.

关键词： Maximum flow interdiction Stochastic programming Conditional value-at-Risk (CVar) Risk-averse optimization mixed-integer linear programming

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Efficient formulations for dynamic warehouse location under discrete transportation costs

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COMPUTERS & CHEMICAL ENGINEERING 2018年 111卷 311-323页

作者： Brunaud, Braulio Bassett, Matthew H. Agarwal, Anshul Wassick, John M. Grossmann, Ignacio E. Carnegie Mellon Univ Pittsburgh PA 15213 USA Dow AgroSci Indianapolis IN 46268 USA Dow Chem Co USA Freeport TX 77541 USA Dow Chem Co USA Midland MI 48674 USA

A mixed-integer linear programming model is proposed to determine the optimal number, location and capacity of the warehouses required to support a long-term forecast with seasonal demand. Discrete transportation costs, dynamic warehouse contracting, and the handling of safety stock are the three main distinctive features of the problem. Four alternatives for addressing discrete transportation costs are compared. The most efficient formulation is obtained using integer variables to account for the number of units used of each transportation mode. Contracting policies constraints are derived to ensure use of warehouses for continuous periods. Similar constraints are included for the case when a warehouse is closed. Safety stock with risk-pooling effect is considered using a piecewise-linear representation. To solve large-scale problems, tightening constraints, and simplified formulations are proposed. These formulations are based on single-sourcing assumptions and yield near-optimal results with large reduction in the solution time. (c) 2017 Elsevier Ltd. All rights reserved.

关键词： Supply chain design Facility location Discrete transportation cost Safety stock mixed-integer linear programming

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A new approach to electricity market clearing with uniform purchase price and curtailable block orders

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APPLIED ENERGY 2018年 226卷 618-630页

作者： Savelli, Iacopo Cornelusse, Bertrand Giannitrapani, Antonio Paoletti, Simone Vicino, Antonio Univ Siena Dipartimento Ingn Informaz & Sci Matemat Siena Italy Univ Liege Dept Elect Engn & Comp Sci Liege Belgium

The European market clearing problem is characterized by a set of heterogeneous orders and rules that force the implementation of heuristic and iterative solving methods. In particular, curtailable block orders and the uniform purchase price pose serious difficulties. A block order spans over multiple hours, and can be either fully accepted or fully rejected. The uniform purchase price prescribes that all consumers pay a common price in all the zones, while producers receive zonal prices, which can differ from one zone to another. The market clearing problem in the presence of both the uniform purchase price and block orders is a major open issue in the European context. The uniform purchase price scheme leads to a non-linear optimization problem involving both primal and dual variables, whereas block orders introduce multi-temporal constraints and binary variables into the problem. As a consequence, the market clearing problem in the presence of both block orders and the uniform purchase price can be regarded as a non-linear integer programming problem involving both primal and dual variables with complementary and multi-temporal constraints. The aim of this paper is to present a non-iterative and heuristic-free approach for solving the market clearing problem in the presence of both curtailable block orders and the uniform purchase price scheme. The solution is exact, with no approximation up to the level of resolution of current market data. By resorting to an equivalent uniform purchase price formulation, the proposed approach results in a mixed-integer linear program, which is built starting from a non-linear integer bilevel programming problem. Numerical results using real market data are reported to show the effectiveness of the proposed approach. The model has been implemented in Python, and the code is freely available on a public repository.

关键词： Bilevel programming Curtailable block orders European market clearing mixed-integer linear programming Power system economics Uniform purchase price

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Bi-objective optimization of biochar-based carbon management networks

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JOURNAL OF CLEANER PRODUCTION 2018年 188卷 911-920页

作者： Belmonte, Beatriz A. Benjamin, Michael Francis D. Tan, Raymond R. De La Salle Univ Chem Engn Dept 2401 Taft Ave Manila 0922 Philippines Univ Santo Tomas Chem Engn Dept Espana Blvd Manila 1015 Philippines Univ Santo Tomas Res Ctr Nat & Appl Sci Espana Blvd Manila 1015 Philippines

Biochar is the carbon-rich solid product derived from thermochemical processing of biomass. Its application to soil can sequester atmospheric carbon, leading to negative net emissions, while also improving agricultural yield. Biochar-based carbon management networks thus have the potential for scalable contributions to climate change mitigation efforts. However, it is necessary to allocate biochar of suitable quality to appropriate sinks, based on contaminant tolerance limits of soil. In this work, the network is modelled as a bi-objective mixed integer linear programming model, with profit and carbon sequestration as the objective functions. The model calculates the optimum allocation of biochar such that their prescribed limits for the contaminants are met. A Philippine case study is solved under different scenarios to illustrate the practical use of the developed model. The results provide useful insights for the rational decision-maker to arrive at the most preferred solution among the Pareto optimal choices. Comparison of the two scenarios substantiate the significance of unique sequestration factor as an additional parameter in the model to account for the interactions between the soils and biochars so that the maximum sustainable potential of biochar in climate change mitigation can be properly assessed. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Biochar Negative emissions technology Bi-objective optimization Carbon management network Source-sink model mixed-integer linear programming

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Advanced control strategy for an energy storage system in a grid-connected microgrid with renewable energy generation

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IET SMART GRID 2018年第3期1卷 96-103页

作者： Teo, Tiong Teck Logenthiran, Thillainathan Woo, Wai Lok Abidi, Khalid Newcastle Univ Sch Elect & Elect Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

The operating cost of the consumer can be reduced in an electricity market-based environment by shifting consumption to a lower price period. This study presents the design of an advanced control strategy to be embedded in a grid connected microgrid with renewable and energy storage capability. The objectives of the control strategy are to control the charging and discharging rates of the energy storage system to reduce the end-user operating cost through arbitrage operation of the energy storage system and to reduce the power exchange between the main and microgrid. Instead of using a forecasting-based approach, the proposed methodology takes the difference between the available renewable generation and load, state-of-charge of energy storage system and electricity market price to determine the charging and discharging rates of the energy storage system in a rolling horizon. The proposed control strategy is compared with a self-adaptive energy storage system controller and mixed-integer linear programming with the same objectives. Empirical evidence shows that the proposed controller can achieve a lower operating cost and reduce the power exchange between the main and microgrid.

关键词： self-adaptive energy storage system controller grid-connected microgrid Control of electric power systems mixed-integer linear programming charging discharging rates Optimisation techniques linear programming renewable energy storage capability advanced control strategy power exchange power markets end-user operating cost reduction power generation control power grids renewable energy generation discharging rates Power system management, operation and economics integer programming pricing distributed power generation forecasting-based approach adaptive control electricity market-based environment renewable energy sources Self-adjusting control systems Distributed power generation electricity market price energy storage

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On the Location of Fog Nodes in Fog-Cloud Infrastructures

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SENSORS 2019年第11期19卷 2445页

作者： da Silva, Rodrigo A. C. da Fonseca, Nelson L. S. Univ Estadual Campinas UNICAMP IC Av Albert Einstein 1251 BR-13083852 Campinas SP Brazil

In the fog computing paradigm, fog nodes are placed on the network edge to meet end-user demands with low latency, providing the possibility of new applications. Although the role of the cloud remains unchanged, a new network infrastructure for fog nodes must be created. The design of such an infrastructure must consider user mobility, which causes variations in workload demand over time in different regions. Properly deciding on the location of fog nodes is important to reduce the costs associated with their deployment and maintenance. To meet these demands, this paper discusses the problem of locating fog nodes and proposes a solution which considers time-varying demands, with two classes of workload in terms of latency. The solution was modeled as a mixed-integer linear programming formulation with multiple criteria. An evaluation with real data showed that an improvement in end-user service can be obtained in conjunction with the minimization of the costs by deploying fewer servers in the infrastructure. Furthermore, results show that costs can be further reduced if a limited blocking of requests is tolerated.

关键词： fog computing cloud computing facility location mixed-integer linear programming

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mixed-integer programming Model for Profiling Disease Biomarkers from Gene Expression Studies 5th

Mixed-Integer Programming Model for Profiling Disease Biomar...

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5th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO)

作者： Santiago, Andre M. Rocha, Miguel Dourado, Antonio Arrais, Joel P. Univ Minho Dept Informat Braga Portugal Univ Coimbra CISUC Coimbra Portugal

ISBN: (纸本)9783319561547;9783319561530

Biomedical research has seen great advances in recent years, in great part due to the long-term aid of the ability to identify biological or genetic markers that uniquely match a given disease. Despite several successes stories, the reality is that most diseases still lack an effective way of treatment, and even diagnostic. While the emergence of -omic technologies, enabled the screening of a whole cell at the molecular level, the large quantities of data produced restricted the capability to extract valid outcomes. In this paper, we propose an optimization model, based of mixedinteger linear programming, capable of identifying a combination of biomarkers for distinguishing between healthy and diseased samples. The model achieves this taking several individuals' gene expression profiles, identifying the most relevant genes for differentiation and discovering the optimal combination of biomarkers that best explains the difference between both states. This model was validated on two different datasets through sampling analysis, achieving an out of sample accuracy up to 93%.

关键词： Biomarkers Disease diagnostic mixed-integer linear programming

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Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery

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APPLIED ENERGY 2019年 254卷

作者： Roni, Mohammad S. Thompson, David N. Hartley, Damon S. Idaho Natl Lab Data & Software Sci Idaho Falls ID 83402 USA Idaho Natl Lab Bioenergy Technol Dept Idaho Falls ID USA

Conventional practices of siting all biomass preprocessing operations at the biorefinery is widely believed to be the most cost-effective solution for feedstock supply because of economies of scale. However, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as "depots" located near biomass sources. This study presents a comparative case study with multiple biomass resources to analyze biorefinery feedstock supply logistics designs having distributed depots and a primary depot co-located with the biorefinery. A mixed-integer linear programming model was developed to simultaneously optimize feedstock sourcing decisions, and optimal preprocessing depot locations and size, utilizing biomass resources from agricultural residue, energy and municipal solid waste to meet carbohydrate specifications and feedstock demand for a biochemical conversion process. Results from a case study in the US showed that a biorefinery could increase its feedstock supply draw area and supply volume by 57.3%, 177.4% respectively without increasing the feedstock delivered cost by adopting distributed depot-in the feedstock supply chain design. A distributed-depot-based supply chain can be more economical by selecting optimal mix of biomass resource, optimal siting and depot scales during feedstock supply chain design. The findings from this study indicate that a biorefinery can utilize dynamic blending to meet the feedstock quality specifications as well as larger supply radius in the distributed depot-based supply chain design to access more available biomass to handle potential feedstock supply uncertainty.

关键词： Feedstock supply chain mixed-integer linear programming Supply radius Depot Biomass Dynamic blending

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