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检索条件"主题词=Mixed integer linear programming"

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Distributed Model Predictive Control for Rescheduling of Railway Traffic 17

Distributed Model Predictive Control for Rescheduling of Rai...

引用

IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)

作者： Kersbergen, Bart van den Boom, Ton De Schutter, Bart Delft Univ Technol Delft Ctr Syst & Control NL-2600 AA Delft Netherlands

ISBN: (纸本)9781479960781

In this paper we introduce two distributed model predictive control (DMPC) methods for the rescheduling of railway traffic. In each step of the DMPC approach dispatching actions are determined that reduce the amount of delay in the network as much as possible by solving a mixed integer linear programming (MILP) problem. The constraints of the MILP are based on a model of the railway traffic and network and the possible dispatching actions. In the first method each subproblem consists of the complete constraint matrix and the solver tries to minimize the centralized cost function, but can only change a limited number of binary variables (which correspond to the dispatching actions). By limiting the number of binary variables each subproblem is easier to solve than the centralized problem. For the second method each subproblem consists of only a part of the problem and the solver minimizes a local cost function, and it can only change the binary variables for that part of the problem. This reduces the complexity of the subproblems even further, but the solver can not determine the effects of the binary variables on the solution quality of the other subproblems. Both methods significantly reduce the time needed to determine the dispatching actions. The average time needed to compute the solution is 11.56 times shorter when using method 1 and 39.11 times shorter when using method 2. The solution found is on average only 0.6 3 % less optimal for method 1 and 1.27 % less optimal for method 2.

关键词： distributed control integer programming linear programming matrix algebra predictive control rail traffic control DMPC approach binary variables centralized cost function constraint matrix dispatching actions distributed model predictive control mixed integer linear programming railway traffic rescheduling Cost function Delays Dispatching Predictive control Predictive models Rail transportation Vectors

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Centralized Non-Convex Model Predictive Control for Cooperative Collision Avoidance of Networked Vehicles

Centralized Non-Convex Model Predictive Control for Cooperat...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： Alrifaee, Bassam Mamaghani, Masoumeh Ghanbarpour Abel, Dirk Rhein Westfal TH Aachen Dept Mech Engn Inst Automat Control D-52074 Aachen Germany Rhein Westfal TH Aachen Dept Elect Engn D-52074 Aachen Germany

ISBN: (纸本)9781479974061

This paper presents a novel design of a collision avoidance controller of networked vehicles using a centralized Model Predictive Control (MPC) concept. The primary objective is to avoid collisions. The secondary objective is dealing with the quality of the collision-free trajectory, which is defined in comparison to the predefined reference trajectory. The resulted optimization problem is non-convex due to collision avoidance constraints. Two different methods to solve this non-convex program are presented, mixed integer linear programming (MILP) and convex relaxation. In MILP, using binary variables and the big-M method, the avoidance constraints can be formulated naturally. The other method is Semi-Definite programming (SDP) relaxation. First, the optimization problem is formulated in the form of a quadratically constrained quadratic program, then it is solved using the SDP relaxation.

关键词： collision avoidance linear programming predictive control quadratic programming road vehicles trajectory control MILP MPC SDP relaxation big-M method collision avoidance controller collision-free trajectory constrained quadratic program cooperative collision avoidance mixed integer linear programming model predictive control networked vehicles optimization predefined reference trajectory semidefinite programming relaxation Collision avoidance Equations linear programming Mathematical model Optimization Trajectory Vehicles Collision avoidance Predictive control linear programming mixed integer linear programming quadratic programming vehicle trajectory control road vehicles trajectory Maximum Allowable Concentration Model predictive control Non-Convex Mathematical Model Land transportation

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A new concept for the clearing of European Power Exchange day-ahead markets with complex orders

A new concept for the clearing of European Power Exchange da...

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11th International Conference on European Energy Market (EEM)

作者： Dourbois, G. A. Biskas, P. N. Vlachos, A. G. Aristotle Univ Thessaloniki Dept Elect & Comp Engn Thessaloniki 54124 Greece Regulatory Author Energy GR-11854 Athens Greece

ISBN: (纸本)9781479960958

A new concept for the clearing of the day-ahead market of a European Power Exchange is proposed in this paper, bypassing the problems caused by the indivisibility of complex orders present in the European markets. The presence of complex orders may lead to paradoxically accepted and/or paradoxically rejected orders, necessitating the use of iterative heuristic procedures and empirical simplifying criteria for their handling. In this paper, the concept of "adjustable orders" is introduced, leading to a significant simplification in the handling of complex orders. The adjustable orders can be partially cleared, leading to orders that can be marginally accepted in the market clearing, setting the market prices accordingly for the hours involved in the orders. The complex orders that are used in this paper comprise profile block orders (offers/bids), flexible hourly orders and joint demand profile orders. The modeling of adjustable blocks is not possible as a MILP problem due to the inherent indivisibility denoted by the use of binary variables;instead, the day-ahead market clearing is formulated as a mixed Complementarity Problem. The solution of the proposed MCP model is compared with the solution of the classical MILP model solution within an iterative procedure (employed in CWE and Nordpool) for the handling of paradoxically accepted/rejected orders.

关键词： Day-ahead Electricity Market Power Exchange Adjustable Orders Paradoxically Accepted/Rejected Orders mixed Complementarity Problem mixed integer linear programming

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An MILP Model for the Plug-In Electric Vehicle Charging Coordination Problem in Electrical Distribution Systems

An MILP Model for the Plug-In Electric Vehicle Charging Coor...

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IEEE PES General Meeting

作者： Franco, John F. Rider, Marcos J. Romero, Ruben Univ Estadual Paulista Fac Engn Ilha Solteira Dept Elect Engn Ilha Solteira SP Brazil

ISBN: (纸本)9781479964154

A new mixed-integer linear programming (MILP) model is proposed to represent the plug-in electric vehicles (PEVs) charging coordination problem in electrical distribution systems. The proposed model defines the optimal charging schedule for each division of the considered period of time that minimizes the total energy costs. Moreover, priority charging criteria is taken into account. The steady-state operation of the electrical distribution system, as well as the PEV batteries charging is mathematically represented;furthermore, constraints related to limits of voltage, current and power generation are included. The proposed mathematical model was applied in an electrical distribution system used in the specialized literature and the results show that the model can be used in the solution of the PEVs charging problem.

关键词： Electrical distribution system plug-in electric vehicles mixed integer linear programming optimal charging

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Fair Resource Allocation in Multiuser OFDMA Downlink with Passive Eavesdropping 10

Fair Resource Allocation in Multiuser OFDMA Downlink with Pa...

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10th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Karachontzitis, Sotiris Timotheou, Stelios Krikidis, Ioannis Berberidis, Kostas Univ Patras Comp Engn & Informat Dept Patras Greece Univ Patras RACTU RU 8 Patras Greece Univ Cyprus Dept Elect & Comp Engn Nicosia Cyprus Univ Cyprus KIOS Res Ctr Intelligent Syst & Networks Nicosia Cyprus

ISBN: (纸本)9781479950416

In this paper, we study the problem of resource allocation for a multiuser orthogonal frequency-division multiple access (OFDMA) downlink with eavesdropping. The considered setup consists of a base station, several users and a single eavesdropper that indents to wiretap the transmitted message within each OFDMA subchannel. By taking into consideration the existence of the eavesdropper, the base station aims to assign subchannels and allocate the available power in order to optimize the max-min fairness criterion over the users' secrecy rate. The investigated problem is hard to be solved because of its combinatorial and nonlinear nature. Thus, optimality is discussed for two particular cases where the available power tends to infinity and zero, respectively. The optimal solution is obtained by formulating a mixed integer linear problem in the first case and a series of linear sum assignment problems in the second. In addition, two low-complexity solutions are presented which are based on decoupling the subchannel and the power allocation subproblems. Numerical results are provided to illustrate the performance of the presented solutions.

关键词： Resource allocation physical layer security mixed integer linear programming linear sum assignment problem

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Further Developments with Perturbation Techniques to Protect Tabular Data

Further Developments with Perturbation Techniques to Protect...

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UNESCO Chair in Data Privacy International Conference on Privacy in Statistical Databases (PSD)

作者： Hernandez-Garcia, Maria-Salome Salazar-Gonzalez, Juan-Jose Univ La Laguna Tenerife Spain

ISBN: (纸本)9783319112572;9783319112565

Statistical agencies collect input data from individuals and deliver output information to the society based on these data. A fundamental feature of output information is the "protection" of sensitive information, since too many details could disseminate privacy information from individuals and therefore violate their rights. Another feature of output information is the "utility" to data users, as a scientific may use this output for research or a politician for making decisions. Clearly more details are in the output, more useful it is, but it is also less protected. There are several methodologies based on Mathematical Optimization to solve the problem of finding "good" protected and useful solutions. While the literature on algorithms to apply them is extensive, statisticians have major concerns to use them in practice because these algorithms may have numeral troubles on frequency tables and may produce biased solutions. This article discusses these observations and describes how to overcome them using a modern technique called Enhanced Controlled Tabular Adjustment. Computational experiments show the effectiveness of the approach on benchmark instances.

关键词： mixed integer linear programming Controlled Tabular Adjustment Tabular Data Protection Unbiased Methods

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Optimal multi-agent planning solution for a sample gathering problem

Optimal multi-agent planning solution for a sample gathering...

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IEEE 19th International Conference on Automation, Quality and Testing, Robotics (THETA)

作者： Burlacu, Adrian Kloetzer, Marius Ostafi, Florin Gheorghe Asachi Tech Univ Iasi Dept Automat Control & Appl Informat Iasi Romania

ISBN: (纸本)9781479937325

This research targets the problem of automatically planning a team of mobile agents such that they collect the samples scattered throughout an environment in minimum time. Each mobile agent can carry at most one sample at a time and it can travel a maximum total distance, given by agent's available energy. The environment is assumed already abstracted to a finite graph, where a node plays the role of the deposit where the samples should be gathered. Our solution consists in several steps that lead to a formulation of the initial problem as a mixed integer linear programming one. The solution yields a plan that imposes for each agent the samples and the order for collecting them. This result is optimal from the point of view of collecting all samples in minimum time.

关键词： mixed integer linear programming Mobile agents collection Solutions harvesting Optimal Solution Environments extreme firing range Planning point of view

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Hydrothermal Scheduling Flexibility Enhancement with Pumped-Storage Units 22

Hydrothermal Scheduling Flexibility Enhancement with Pumped-...

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22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Zeynal, Hossein Eidiani, Mostafa KDU Univ Coll Sch Engn Petaling Jaya 47400 Selangor Malaysia Khorasan Inst Higher Educ Fac Engn Mashhad Iran

ISBN: (纸本)9781479944095

this paper presents an efficient MILP algorithm to solve hydrothermal scheduling problem with enhanced flexibility via multiple pumped-storage units. A comprehensive Hydraulic model for pumped-storage and river system constraints is developed. The performance improvement of the proposed algorithm falls in two-fold. First, a piecewise approximation approach is applied throughout all nonlinear functions of the model, representing fully linear HTS model. Second, multi-threadng technology which accelerates the solution process of Branch and Cut method. Simulation results show that the developed linear MIP-HTS algorithm exhibits high performance in terms of objective cost and execution time. Further results demonstrated that implementation of multi-thread parallel programming can further improve the computation time as compared to the serial executions. This, however, allowed one to procure better solution by taking tighter optimality gap that results in more accurate solution.

关键词： Hydrothermal scheduling pumped-storage unit mixed integer linear programming

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Assessing the Information Loss of Controlled Adjustment Methods in Two-Way Tables

Assessing the Information Loss of Controlled Adjustment Meth...

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UNESCO Chair in Data Privacy International Conference on Privacy in Statistical Databases (PSD)

作者： Castro, Jordi Gonzalez, Jose A. Univ Politecn Cataluna Dept Stat & Operat Res ES-08034 Barcelona Spain

ISBN: (纸本)9783319112572;9783319112565

Minimum distance controlled tabular adjustment (CTA) is a perturbative technique of statistical disclosure control for tabular data. Given a table to be protected, CTA looks for the closest safe table by solving an optimization problem using some particular distance in the objective function. CTA has shown to exhibit a low disclosure risk. The purpose of this work is to show that CTA also provides a low information loss, focusing on two-way tables. Computational results on a set of midsize tables validate this statement.

关键词： Statistical disclosure control controlled tabular adjustment information loss data utility mixed integer linear programming

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Joint Discrete Phase-Only Broadcast Beamforming With Antenna Selection

Joint Discrete Phase-Only Broadcast Beamforming With Antenna...

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22nd IEEE Signal Processing and Communications Applications Conference (SIU)

作者： Demir, Ozlem Tugfe Tuncer, T. Engin Orta Dogu Tekn Univ Elekt Elekt Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781479948741

In this paper, single group multicast (broadcast) phase-only transmit beamformer design with antenna subset selection is considered. The problem is converted into a linear form and solved efficiently by using mixed integer linear programming to find the optimum subset of antennas and beamformer vector. Several experiments are done and it is shown that the proposed approach is effective and efficient.

关键词： transmit beamformer discrete beamformer mixed integer linear programming antenna selection

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