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A robust approach to the UAV task assignment problem

INTERNATIONAL JOURNAL OF ROBUST AND NONlinear CONTROL 2008年第2期18卷 118-134页

作者： Alighanbari, Mehdi How, Jonathan P. MIT Aerosp Controls Lab Cambridge MA 02139 USA

This paper presents a new robust approach to the task assignment of unmanned aerial vehicles (UAVs) operating in uncertain dynamic environments for which the optimization data, such as target cost and target-UAV distances, are time varying and uncertain. The impact of this uncertainty in the data is mitigated by tightly integrating two approaches for improving the robustness of the assignment algorithm. One approach is to design task assignment plans that are robust to the uncertainty in the data, which reduces the sensitivity to errors in the situational awareness (SA), but can be overly conservative for long duration plans. A second approach is to replan as the SA is updated, which results in the best plan given the current information, but can lead to a churning type of instability if the updates are performed too rapidly. The strategy proposed in this paper combines robust planning with the techniques developed to eliminate churning. This combination results in the robust filter-embedded task assignment algorithm that uses both proactive techniques that hedge against the uncertainty, and reactive approaches that limit churning behavior by the vehicles. Numerous simulations are shown to demonstrate the performance benefits of this new algorithm. Copyright (c) 2007 John Wiley & Sons, Ltd.

关键词： robust planning under uncertainty unmanned aerial vehicles UAV task assignment mixed-integer linear programming

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Electricity markets cleared by merit order - Part I: Finding the market outcomes supported by pure strategy Nash equilibria

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IEEE TRANSACTIONS ON POWER SYSTEMS 2008年第2期23卷 361-371页

作者： Hasan, Ebrahim Galiana, Francisco D. Conejo, Antonio J. McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 2A7 Canada Univ Castilla La Mancha Dept Elect Engn E-13071 Ciudad Real Spain

In an electricity market cleared by a merit-order economic dispatch we first identify the necessary conditions for the market outcomes supported by pure strategy Nash equilibria (NE) to exist when generating companies (Gencos) game through their incremental cost offers or supply functions. A Genco may own any number of units, each offering to generate power through an incremental cost curve or supply function consisting of multiple blocks. Then, we develop a mixed-integer linear programming (MILP) scheme to find the NE without approximations or iterations. In Part II of this paper, we show how to use these NE to derive a dominant offer strategy in terms of gaming or not gaming that best meet the risk/benefit expectations of the participating Gencos. The MILP scheme is tested on several systems of up to 30 generating units, each with four incremental cost blocks. Finally, based on these results, we carry out a number of numerical analyses of how market power is influenced by the number and size of the competing Gencos.

关键词： electricity markets gaming market outcomes market power merit order mixed-integer linear programming pure strategy Nash equilibria strategic offers supply function equilibrium

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Piecewise MILP under- and overestimators for global optimization of bilinear programs

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AICHE JOURNAL 2008年第4期54卷 991-1008页

作者： Wicaksono, Danan Suryo Karimi, I. A. Natl Univ Singapore Dept Chem & Biomol Engn Singapore 117576 Singapore

Many practical problems of interest in chemical engineering and other fields can be formulated as bilinear programs (BLPs). For such problems, a local nonlinear programming solver often provides a suboptimal solution or even fails to locate a feasible one. Numerous global optimization algorithms devised for bilinear programs rely on linear programming (LP) relaxation, which is often weak, and, thus, slows down the convergence rate of the global optimization algorithm. All interesting recent development is the idea of using an ab initio partitioning of the. search domain to improve the relaxation quality, which results in a relaxation problem that is a mixed-integer linear program (MILP) rather than LP, called as piecewise MILP relaxation. However, much work is in order to fully exploit the potential of such approach. Several novel formulations are developed for piecewise MILP under- and overestimators for BLPs via three systematic approaches, and two segmentation schemes. As is demonstrated and evaluated the superiority of the novel models is shown, using a variety of examples. In addition, metrics are defined to measure the effectiveness of piecewise MILP relaxation within a two-level-relaxation framework, and several theoretical results are presented, as well as valuable insights into the properties of such relaxations, which may prove useful in developing global optimization algorithms. (c) 2008 American Institute of Chemical Engineers.

关键词： global optimization bilinear programming mixed-integer linear programming piecewise under- and overestimators process network synthesis

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Prediction of secondary structures of proteins using a two-stage method

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COMPUTERS & CHEMICAL ENGINEERING 2008年第1-2期32卷 78-88页

作者： Yueksektepe, Fadime Ueney Yilmaz, Oezlem Tuerkay, Metin Koc Univ Coll Engn TR-34450 Istanbul Turkey

Protein structure determination and prediction has been a focal research subject in life sciences due to the importance of protein structure in understanding the biological and chemical activities of organisms. The experimental methods used to determine the structures of proteins demand sophisticated equipment and time. A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. However, prediction accuracies of these methods rarely exceed 70%. In this paper, a novel two-stage method to predict the location of secondary structure elements in a protein using the primary structure data only is presented. In the first stage of the proposed method, the folding type of a protein is determined using a novel classification approach for multi-class problems. The second stage of the method utilizes data available in the Protein Data Bank and determines the possible location of secondary structure elements in a probabilistic search algorithm. It is shown that the average accuracy of the predictions is 74.1 % on a large structure dataset. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： protein secondary structure prediction data classification mixed-integer linear programming

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Optimal production scheduling for the dairy industry

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ANNALS OF OPERATIONS RESEARCH 2008年第1期159卷 315-331页

作者： Doganis, Philip Sarimveis, Haralambos Natl Tech Univ Athens Sch Chem Engn Athens 15780 Greece

The increasing variety of products offered by the food industry has helped the industry to respond to market trends, but at the same time has resulted in a more complex production process, which requires flexibility and an efficient coordination of existing resources. Especially in industrial yogurt production, there is a wide variety of products that differ in features like fat content, the whey used to produce the mixture, the flavor, the size of the container or the language on the label. The great diversification and the special features that characterize yogurt production lines (satisfaction of multiple due dates, variable processing times, sequence-dependent setup times and costs and monitoring of inventory levels), render generic scheduling methodologies impractical for real-world applications. In this work we present a customized mixed integer linear programming (MILP) model for optimizing yogurt packaging lines that consist of multiple parallel machines. The model is characterized by parsimony in the utilization of binary variables and necessitates the use of only a small pre-determined number of time periods. The efficiency of the proposed model is illustrated through its application to the yogurt production plant of a leading dairy product manufacturing company in Greece.

关键词： parallel machines scheduling yogurt packaging optimization mixed-integer linear programming

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The Block Planning Approach: A Case Study Application from the Beverage Industry

The Block Planning Approach: A Case Study Application from t...

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International Conference on Industrial Engineering and Engineering Management

作者： Guenther, H. O. Berlin Inst Technol Dept Prod Management Berlin Germany

ISBN: (纸本)9781424426294

Block planning is a specific concept for the development of production schedules based on the definition of setup families and the production of product variants in a pre-defined sequence. In process industries, e.g. in the production of beverages, there is often a natural sequence in which the various products are to be produced in order to minimize total changeover time and to maintain product quality standards. In this type of industry, the predominant type of production system is "make-and-pack", i.e. the final bottling and packaging lines determine the output rate of the entire production system. A mixed-integer linear optimization (MILP) model is proposed that determines the size and the time phasing of the individual production lots while observing capacity constraints of the various production lines and assuring the coverage of daily demand elements.

关键词： Production scheduling block planning mixed-integer linear programming beverage industry

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Bidding wind power in short-term electricity market based on multiple-objective fuzzy optimization

Bidding wind power in short-term electricity market based on...

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Canadian Conference on Electrical and Computer Engineering

作者： Xue, Yaosuo Venkatesh, Bala Chang, Liuchen Univ New Brunswick Dept Elect & Comp Engn Fredericton NB Canada

ISBN: (纸本)9781424416424

Wind energy is promising with no fuel cost and zero greenhouse gas emissions;however, its intermittent and volatile nature has added much to operation burdens and thus a low penetration level in short-term or spot market. On the one hand, the power system operator is facing increased spinning reserve and generation uncertainty;on the other hand, the wind independent power producer (IPP) is subject to imbalance penalties in the balancing market. Previous literatures solely focused on maximizing the profit for a wind IPP formulating optimal bidding strategies without the consideration of operator side. This paper proposes a multiple-objective optimal bidding strategy to achieve both wind IPP's maximum profit and less challenge for the operator. The strategy is formulated as a mixed-integer linear programming (MILP) problem with fuzzy optimization techniques. Analytic and numerical solutions will be given with discussion on risk control.

关键词： optimal bidding strategy wind power fuzzy optimization mixed-integer linear programming

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Dynamic reconfiguration of logical topology for WDM networks under traffic changes

Dynamic reconfiguration of logical topology for WDM networks...

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IEEE Network Operations and Management Symposium

作者： Tran, Phuong Nga Killat, Ulrich Hamburg Univ Technol Commun Networks Dept Hamburg Germany

ISBN: (纸本)9781424420650

In this paper, we present a new approach to solve the logical topology reconfiguration problem for IP over WDM networks under dynamic traffic. Based on the measurement of lightpaths' load, a change in the logical topology is made if some lightpath is highly loaded or under utilized. The change can be adding/deleting several lightpaths or just rerouting traffic in the current logical topology. The key idea of our approach is to determine a new logical topology so that the maximum lightpaths' load at the time of reconfiguration is limited by a load-balance indicator, which is pre-defined as a system's parameter. It ensures the network performance (in terms of lightpath utilization) and also increases the lifetime of the logical topology under dynamic traffic changes. Moreover, our approach ensures no network disruption during the reconfiguration process while allowing adding or deleting multiple lightpaths at the same time. The algorithm is formulated as a mixed integer linear programming (MILP). The performance is investigated and compared with Gencata's approach through an illustrative numerical example. Because the proposed MILP is complex and can be applied only to small networks, an approximate model is also presented to solve the problem for some real-size networks.

关键词： IP over WDM logical topology dynamic reconfiguration mixed-integer linear programming

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Using a Mathematical programming Modeling Language for Optimal CTA

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International Conference on Privacy in Statistical Databases

作者： Castro, Jordi Baena, Daniel Univ Politecn Cataluna Dept Stat & Operat Res Jordi Girona 1-3 ES-08034 Barcelona Catalonia Spain Inst Estadist Catalunya Barcelona 08003 Catalonia Spain

ISBN: (纸本)9783540874706

Minimum-distance controlled tabular adjustment methods (CTA) have been formulated as an alternative to the cell suppression problem (CSP) for tabular data. CTA formulates an optimization problem with fewer variables and constraints than CSP. However, the inclusion of binary decisions about protection sense of sensitive cells (optimal CTA) in the formulation, still results in a mixed integer-linear problem. This work shows how mathematical programming modeling languages can be used to develop a prototype for optimal CTA based on Benders method. Preliminary results are reported for some medium size two-dimensional tables. For this type of tables, the approach is competitive with other general-purpose algorithms implemented in commercial solvers.

关键词： statistical disclosure control controlled tabular adjustment mixed-integer linear programming Benders decomposition

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An Efficient Method for Optimal Location and Sizing of Fixed and Switched Shunt Capacitors in Large Distribution Systems

An Efficient Method for Optimal Location and Sizing of Fixed...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Khodr, H. M. Yusta, J. M. Vale, Zita Ramos, Carlos ISEP IPP Elect Engn Inst Porto Knowledge Engn & Decis Support Res Grp GECAD Rua Dr Antonio Bernardino Almeida 431 P-4200072 Oporto Portugal Univ Zaragoza Dept Elect Engn E-50018 Zaragoza Spain

ISBN: (纸本)9781424419050

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.(1)

关键词： distribution systems capacitor placement large-scale optimization mixed-integer linear programming

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