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检索条件"任意字段=17th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2014"

共 43 条记录，以下是31-40 订阅

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Autonomous Lane-Change Controller via Mixed Logical Dynamical

Autonomous Lane-Change Controller via Mixed Logical Dynamica...

引用

IEEE international conference on Intelligent Transportation Systems

作者： Yaoqiong Du Yizhou Wang Ching-Yao Chan Dept. of Mech. Eng. Univ. of California Berkeley Berkeley CA USA

ISBN: (纸本)9781479960798

this paper focuses on the design of a model based methodology to optimize lane change maneuvers based on the predictions of neighboring agents. In particular, the dynamics of vehicles are modeled as double integrators, and the lane change actions are indicated by boolean variables while neglecting the lane change dynamics. the objective of the optimal control is to minimize the travel time, maintain saftey distances between the target vehicle and neighboring ones, satisfy the operational constraints of the target vehicle, and comply with the speed limit. the control problem is formulated as a mixed logic dynamic system, and solved by Cplex, a commercial mixed integer optimization solver. Finally, the effectiveness of the proposed methodology is demonstrated by two simulated scenarios in this paper.

关键词： Boolean functions integer programming minimisation mobile robots optimal control road traffic control vehicle dynamics Boolean variables Cplex autonomous lane-change controller commercial mixed integer optimization solver control problem double integrators lane change actions lane change dynamics lane change maneuver optimization mixed logic dynamic system mixed logical dynamical model based methodology neighboring agent predictions travel time minimization Acceleration Decision making optimization Safety Trajectory Vehicle dynamics Vehicles

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Integrated data association and bias estimation in the presence of missed detections

Integrated data association and bias estimation in the prese...

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international conference on Information Fusion

作者： Hongyan Zhu Chen Wang Wen Jiang Chongzhao Han Yan Lin School of Electronic & Information Engineering Xi'an Jiaotong University Xi'an China School of Electronics and Information Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781479916344

this paper is concerned with performing the measurement-to-measurement association and bias estimation jointly in the presence of missed detections. An integrated mix integer programming (MINLP) model is established to determine the correspondence between local measurements and estimate sensor biases simultaneously. An alternation optimization mechanism is employed to solve the complicated MINLP model. A recursive version for bias estimation is developed that provides an access to deal with the measurement data sequentially. Monte Carlo simulation results are presented to illustrate our findings, as also demonstrating the effectiveness of the proposed approach.

关键词： Estimation optimization Educational institutions Joints Time measurement Measurement uncertainty Azimuth

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A bus lane reservation problem in urban bus transit network

A bus lane reservation problem in urban bus transit network

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IEEE international conference on Intelligent Transportation Systems

作者： Peng Wu F. Chu Ada Che Qin Shi Laboratory IBISC University of Evry-Val d'Essonne Evry France School of Management Northwestern Polytechnical University Xi'an China school of Transportation Engineering Hefei University of Technology Anhui China

this work studies a new variant of lane reservation problem called a bus lane reservation problem. It aims to optimally select some road segments to be reserved for buses in a predetermined bus transit network such that bus travelers can be rapidly transited. Two realistic assumptions are made in this work: 1) the total travel time on each bus route should be completed within a given deadline;2) a lane on a road segment can be reserved for buses only when the bus volume on it exceeds a given level. the former guarantees bus travel time in order to improve the service level of a bus transit system. the second ensures minimum bus utilization on a reserved lane. However, private vehicles are not allowed to pass the bus exclusive lanes. Such a bus lane reservation strategy causes negative traffic impact on private vehicles. the objective of the problem is to minimize the negative traffic impact of reserved lanes. For the problem, we first construct an integer linear programming model and demonstrate its complexity to be NP-hard. then, we propose a cut-and-solve algorithm to obtain its optimal solution. the computational results on randomly generated instances show that the proposed method is more efficient than the optimization software CPLEX 12.4.

关键词： Roads Algorithm design and analysis Educational institutions Vehicles integer linear programming Computational modeling

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Airport Surface Trajectory optimization Considering Runway Exit Selection

Airport Surface Trajectory Optimization Considering Runway E...

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IEEE international conference on Intelligent Transportation Systems

作者： Peng Cheng Xiang Zou Wenda Liu department of Automation Civil Aircraft Flight Simulation

the efficiency of taxiing process has become an important factor that restricts the full use of airport runway capacity. this paper investigates the taxiway planning problem. Different from existing related literatures which do not consider the runway exit selecting problem, the significance of runway exit selection for landing aircrafts is discussed. We propose a new conception, Runway Exit Availability (REA), to measure the probability that a flight clear the runway from a specific exit. Applying with REA, we can assign a proper exit to each landing flight. Besides, we construct a time-space network for the airport taxiing system. A mixed integer programming model based on this network is proposed for the assignment of 4D taxiing trajectories - routes and times. With taxiway operations of Beijing Capital international Airport as the testing background, experimental analysis shows that, the scheduling result by considering runway exit selection is superior to the result when exit selection is not considered and the calculation time of the scheduling process is acceptable for application in real systems.

关键词： Atmospheric modeling Equations Availability Airports Aircraft Mathematical model Planning

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A Data-Driven Method for Stochastic Shortest Path Problem

A Data-Driven Method for Stochastic Shortest Path Problem

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IEEE international conference on Intelligent Transportation Systems

作者： Zhiguang Cao Hongliang Guo Jie Zhang Dusit Niyato Ulrich Fastenrath School of Computer Engineering Nanyang Technological University Singapore Traffic information management and routing optimization at BMW Group Munich Germany

this paper aims at solving a stochastic shortest path problem. the objective is to determine an optimal path which maximizes the probability of arriving on time given a time constraint (i.e., a deadline). To solve this problem, we propose a data-driven approach. We first reformulate the original finding optimal path problem as a cardinality minimization problem. then, we apply an L_1 norm minimization technique to solve the cardinality problem. the problem is transformed into a mix integer linear programming problem, which can be solved using standard solvers. this proposed approach has three advantages over the traditional methods: (1) the proposed approach can handle various or even unknown travel time distributions, while traditional stochastic routing algorithms can only work on specified distributions;(2) the proposed approach does not rely on the assumption that the travel time on different road segments is independent from each other;(3) unlike other existing approaches which require that the deadline must be larger than a certain value, the proposed approach can support more flexible deadline definition. then we test our approach respectively on artificial and real-world road networks, the experimental results show that the proposed approach can achieve a comparatively high accuracy when the sampling size of travel time is large enough. Moreover, under some reasonable assumptions, the accuracy could be 100%.

关键词： Minimization Roads Accuracy Shortest path problem Routing optimization Stochastic processes

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Airport Surface Trajectory optimization Considering Runway Exit Selection

Airport Surface Trajectory Optimization Considering Runway E...

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17th international IEEE conference on Intelligent Transportation Systems & the Asia-Pacific Council on Systems Engineering conference 2014

作者： Peng Cheng Xiang Zou Wenda Liu the department of Automation Tsinghua University and with State Key Laboratory of Civil Aircraft Flight Simulation China Galaxy Securities

the efficiency of taxiing process has become an important factor that restricts the full use of airport runway *** paper investigates the taxiway planning *** from existing related literatures which do not consider the runway exit selecting problem,the significance of runway exit selection for landing aircrafts is *** propose a new conception,Runway Exit Availability(REA),to measure the probability that a flight clear the runway from a specific *** with REA,we can assign a proper exit to each landing ***,we construct a time-space network for the airport taxiing system.A mixed integer programming model based on this network is proposed for the assignment of 4D taxiing trajectories- routes and *** taxiway operations of Beijing Capital international Airport as the testing background,experimental analysis shows that,the scheduling result by considering runway exit selection is superior to the result when exit selection is not considered and the calculation time of the scheduling process is acceptable for application in real systems.

关键词： Airport Surface Trajectory optimization Considering Runway Exit Selection

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A Data-Driven Method for Stochastic Shortest Path Problem

A Data-Driven Method for Stochastic Shortest Path Problem

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17th international IEEE conference on Intelligent Transportation Systems & the Asia-Pacific Council on Systems Engineering conference 2014

作者： Zhiguang Cao NTU(ERI N),Interdisciplinary Graduate School,Nanyang Technological University,Singapore Hongliang Guo Jie Zhang Dusit Niyato Ulrich Fastenrath the Energy Research Institute the School of Computer Engineering Nanyang Technological University Singapore head of traffic information management and routing optimization at BMW Group

this paper aims at solving a stochastic shortest path *** objective is to determine an optimal path which maximizes the probability of arriving on time given a time constraint(i.e.,a deadline).To solve this problem,we propose a data-driven *** first reformulate the original finding optimal path problem as a cardinality minimization ***,we apply an L1 norm minimization technique to solve the cardinality *** problem is transformed into a mix integer linear programming problem,which can be solved using standard *** proposed approach has three advantages over the traditional methods:(1) the proposed approach can handle various or even unknown travel time distributions,while traditional stochastic routing algorithms can only work on specified distributions;(2) the proposed approach does not rely on the assumption that the travel time on different road segments is independent from each other;(3) unlike other existing approaches which require that the deadline must be larger than a certain value,the proposed approach can support more flexible deadline *** we test our approach respectively on artificial and real-world road networks,the experimental results show that the proposed approach can achieve a comparatively high accuracy when the sampling size of travel time is large ***,under some reasonable assumptions,the accuracy could be 100%.

关键词： A Data-Driven Method for Stochastic Shortest Path Problem

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An Iterative Scheme for Valid Polynomial Inequality Generation in Binary Polynomial programming

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15th international conference on integer programming and combinatorial optimization (ipco)

作者： Ghaddar, Bissan Vera, Juan C. Anjos, Miguel F. Univ Waterloo Dept Management Sci Waterloo ON N2L 3G1 Canada Tilburg Univ Tilburg Sch Econ & Management Tilburg Netherlands Ecole Polytech Dept Math & Genie Ind Montreal PQ H3T 1J4 Canada Ecole Polytech Gerad Montreal PQ H3T 1J4 Canada

ISBN: (纸本)9783642208072

Semidefinite programming has been used successfully to build hierarchies of convex relaxations to approximate polynomial programs. this approach rapidly becomes computationally expensive and is often tractable only for problems of small sizes. We propose an iterative scheme that improves the semidefinite relaxations without incurring exponential growth in their size. the key ingredient is a dynamic scheme for generating valid polynomial inequalities for general polynomial programs. these valid inequalities are then used to construct better approximations of the original problem. As a result, the proposed scheme is in principle scalable to large general combinatorial optimization problems. For binary polynomial programs, we prove that the proposed scheme converges to the global optimal solution for interesting cases of the initial approximation of the problem. We also present examples illustrating the computational behaviour of the scheme and compare it to other methods in the literature.

关键词： Binary Polynomial programming Binary Quadratic programming Valid Inequality Generation Semidefinite programming

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integer programming and combinatorial optimization 2011

引用

丛书名： Lecture Notes in Computer Science

2011年

作者： Oktay Günlük Gerhard J. Woeginger

ISBN: (数字)9783642208072

ISBN: (纸本)9783642208065

this book constitutes the proceedings of the 15th international conference on integer programming and combinatorial optimization, ipco 2011, held in New York, USA in June 2011. the 33 papers presented were carefully reviewed and selected from 110 submissions. the conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization with the aim to present recent developments in theory, computation, and applications. the scope of ipco is viewed in a broad sense, to include algorithmic and structural results in integer programming and combinatorial optimization as well as revealing computational studies and novel applications of discrete optimization to practical problems.

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Mixed integer linear programming for exact finite-horizon planning in decentralized pomdps

Mixed integer linear programming for exact finite-horizon pl...

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ICAPS 2007, 17th international conference on Automated Planning and Scheduling

作者： Aras, Raghav Dutech, Alain Charpillet, Francois INRIA-Lorraine/Loria 615 rue du Jardin Botanique 54602 Villers-lès-Nancy France

ISBN: (纸本)9781577353447

We consider the problem of finding an n-agent jointpolicy for the optimal finite-horizon control of a decentralized Pomdp (Dec-Pomdp). this is a problem of very high complexity (NEXP-hard in n ≥ 2). In this paper, we propose a new mathematical programming approach for the problem. Our approach is based on two ideas: First, we represent each agent's policy in the sequence-form and not in the tree-form, thereby obtaining a very compact representation of the set of joint-policies. Second, using this compact representation, we solve this problem as an instance of combinatorial optimization for which we formulate a mixed integer linear program (MILP). the optimal solution of the MILP directly yields an optimal joint-policy for the Dec-Pomdp. Computational experience shows that formulating and solving the MILP requires significantly less time to solve benchmark Dec-Pomdp problems than existing algorithms. For example, the multi-agent tiger problem for horizon 4 is solved in 72 sees with the MILP whereas existing algorithms require several hours to solve it. Copyright © 2007, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： integer programming

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