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American Control Conference

作者： Zhong, Zhixia You, Fengqi Northwestern Univ Dept Chem & Biol Engn Evanston IL 60208 USA

ISBN: (纸本)9781479932740

In this work, we proposed novel parametric algorithms for solving large-scale mixed-integer linear and nonlinear fractional programming problems, and illustrate their application in process systems engineering. By developing an equivalent parametric formulation of the general mixed-integer fractional program (MIFP), we propose four exact parametric algorithms based on the root-finding methods, including bisection method, Newton's method, secant method and false position method, respectively, for the global optimization of MIFPs. We also propose an inexact parametric algorithm that can potentially outperform the exact parametric algorithms for some types of MIFPs. Extensive computational studies are performed to demonstrate the efficiency of these parametric algorithms and to compare them with the general-purpose mixed-integer nonlinear programming methods. The applications of the proposed algorithms are illustrated through a case study on process scheduling. Computational results show that the proposed exact and inexact parametric algorithms are more computationally efficient than several general-purpose solvers for solving MIFPs.

关键词： Algorithm design and analysis Computational efficiency Linear programming optimization Productivity Programming Testing Computational methods Numerical algorithms optimization algorithms

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Overview of nonlinear programming methods suitable for calibration of traffic flow models

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OPERATIONAL RESEARCH 2015年第3期15卷 327-336页

作者： Kontorinaki, Maria Spiliopoulou, Anastasia Papamichail, Ioannis Papageorgiou, Markos Tyrinopoulos, Yannis Chrysoulakis, John Tech Univ Crete Dynam Syst & Simulat Lab Khania 73100 Greece TEI Athens Dept Civil & Infrastruct Engn Athens 12210 Greece

The calibration of a macroscopic traffic flow model aims at enabling the model to reproduce, as accurately as possible, the real traffic conditions on a motorway network. Essentially, this procedure targets the best value for the parameter vector of the model and this can be achieved using appropriate optimization algorithms. The parameter calibration problem is formulated as a nonlinear, non-convex, least-squares optimization problem, which is known to attain multiple local minima;for this reason gradient-based solution algorithms are not considered to be an option. The methodologies that are more appropriate for application to this problem are mainly some meta-heuristic algorithms which use direct search approaches that allow them to avoid bad local minima. This paper presents an overview of the most suitable nonlinear programming methods for the calibration procedure of macroscopic traffic flow models. Furthermore, an application example, where two well-known macroscopic traffic flow models are evaluated through the calibration procedure, is presented.

关键词： Traffic flow Calibration Simulation Validation optimization algorithms

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A Column Generation Based Hyper-Heuristic to the Bus Driver Scheduling Problem

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DISCRETE DYNAMICS IN NATURE AND SOCIETY 2015年第Pt.1期2015卷 10-10页

作者： Li, Hong Wang, Ying Li, Shi Li, Sujian Univ Sci & Technol Sch Mech Engn Beijing 100083 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China Univ Technol Belfort Montbeliard Lab Syst & Transports F-90000 Belfort France

Public transit providers are facing continuous pressure to improve service quality and reduce operating costs. Bus driver scheduling is among the most studied problems in this area. Based on this, flexible and powerful optimization algorithms have thus been developed and used for many years to help them with this challenge. Particularly, real-life large and complex problem instances often need new approaches to overcome the computational difficulties in solving them. Thus, we propose a column generation based hyper-heuristic for finding near-optimal solutions. Our approach takes advantages of the benefits offered by heuristic method since the column selection mode is driven by a hyper-heuristic using various strategies for the column generation subproblem. The performance of the proposed algorithm is compared with the approaches in the literature. Computational results on real-life instances are presented and discussed.

关键词： optimization algorithms BUS DRIVER Column

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From Certification of algorithms to Certified MPC: The Missing Links

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IFAC-PapersOnLine 2015年第23期48卷 65-72页

作者： Alamir, Mazen Gipsa-lab CNRS-Control Systems Department University of Grenoble France

Deriving certification bounds for optimization algorithms is an active research area in the control community. This is mainly impulsed by the use of on-line optimization algorithms in real-time MPC through limited computation power. However, the way such bounds are then used to derive a convergence certification for MPC frameworks is still not suficiently mature. This paper contributes in clarifying what are the unavoidable additional ingredients that need to be combined with any algorithm's certification bound in order to derive a relevant certification result for the MPC-based closed-loop performance. Moreover, the paper gives such a general certification result based on these ingredients for any pair of certified algorithm and provably stable ideal MPC formulation. The proposed framework is then instantiated to the particular case of linear MPC and a simple example is given to illustrate the introduced concepts. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： optimization Real time control Certified algorithms Closed loop performance Computation power MPC Certification Online optimization optimization algorithms Real time implementations State dependent

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A numerical method to optimise the spatial dose distribution in carbon ion radiotherapy planning

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RADIATION PROTECTION DOSIMETRY 2015年第1-4期166卷 351-355页

作者： Grzanka, L. Korcyl, M. Olko, P. Waligorski, M. P. R. Inst Nucl Phys PAN Krakow Poland Marie Sklodowska Curie Ctr Oncol Krakow Div Krakow Poland

The authors describe a numerical algorithm to optimise the entrance spectra of a composition of pristine carbon ion beams which delivers a pre-assumed dose-depth profile over a given depth range within the spread-out Bragg peak. The physical beam transport model is based on tabularised data generated using the SHIELD-HIT10A Monte-Carlo code. Depth-dose profile optimisation is achieved by minimising the deviation from the pre-assumed profile evaluated on a regular grid of points over a given depth range. This multi-dimensional minimisation problem is solved using the L-BFGS-B algorithm, with parallel processing support. Another multi-dimensional interpolation algorithm is used to calculate at given beam depths the cumulative energy-fluence spectra for primary and secondary ions in the optimised beam composition. Knowledge of such energy-fluence spectra for each ion is required by the mixed-field calculation of Katz's cellular Track Structure Theory (TST) that predicts the resulting depth-survival profile. The optimisation algorithm and the TST mixed-field calculation are essential tools in the development of a one-dimensional kernel of a carbon ion therapy planning system. All codes used in the work are generally accessible within the libamtrack open source platform.

关键词： TST gene Beams and girders Bragg curve SPATIAL DOSE DISTRIBUTIONS Interpolation Arithmetic Spectra RADIATION DOSE DISTRIBUTIONS optimization algorithms Carbon Ion Radiotherapy Numerical methods instrument design and development PARALLEL PROCESSING (COMPUTERS) field calculation Ions

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Optimized identification method for fractional heating processes on heterogeneous materials

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IFAC-PapersOnLine 2015年第1期28卷 388-389页

作者： Caponetto, Riccardo Sapuppo, Francesca Tomasello, Vincenzo Dipartimento di Ingegneria Elettrica Elettronica e Dei Sistemi Università degli Studi di Catania Catania Italy

An enhanced model for the heating process on heterogeneous materials based on fractional order PDEs has been identified through an optimization algorithm. Experimentation has been carried out on a finite length beam filled with a composite material in order to obtain a model in the frequency domain. The obtained results confirm the fractional nature of the heating processes when diffusion occurs in not continuous composite materials. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Composite materials Frequency domain analysis Heat transfer Models optimization Finite length Fractional order Fractional order systems Frequency domains Heating process Heterogeneous materials Identification method optimization algorithms

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Selection of mother wavelet and decomposition level for energy management in electrical vehicles including a fuel cell

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2015年第45期40卷 15823-15833页

作者： Ibrahim, Mona Jemei, Samir Wimmer, Genevieve Steiner, Nadia Yousfi Kokonendji, Celestin C. Hissel, Daniel Lab Math Besancon F-25030 Besancon France Univ Franche Comte FEMTO ST UMR CNRS 6174 FCLABFR CNRS 3539 F-90010 Belfort France Lab Excellence ACT Lyon France

The Wavelet Transform (WT) is a mathematical method used to represent a given signal in different scales. This method is also used to extract the different frequency bands (or different frequency components) from a signal. In this paper, wavelet transform in the domain of energy management of Electrical Vehicles (EV) is considered. A method for choosing the mother wavelet and the decomposition level will be presented. Taking into account the damages caused by the extreme variations of the power demand on the power sources, this paper shows how Wavelet Transform can help eliminating this negative impact. Copyright (C) 2015, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Electric vehicle Energy management Wavelet transform Power sources optimization algorithms

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Welding diagnostics based on feature selection and optimization algorithms

Welding diagnostics based on feature selection and optimizat...

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Conference on Optical Sensing and Detection

作者： Mirapeix, J. Cobo, A. Garcia-Allende, P. B. Conde, O. M. Lopez-Higuera, J. M. Univ Cantabria Photon Engn Grp E-39005 Santander Spain

ISBN: (纸本)9780819481993

In a previous paper a new approach was explored where the output parameters of a welding monitoring system based on plasma spectroscopy were the participation profiles of plasma ions and neutral atoms. They were obtained by the generation of synthetic spectra and the use of an optimization algorithm, showing correlation to the appearance of defects on the seams. In this work a feature selection algorithm is included in the model to determine the most discriminant wavelengths in terms of defect detection, thus allowing to reduce the spectral range where the synthetic spectra are generated. This should also give rise to an improvement in the overall computational performance of the algorithm. Alternatives to the use of controlled randomn search algorithms will be also explored, and the resulting model will be checked by means of experimental and field tests of arc-welding processes.

关键词： arc-welding on-line monitoring plasma optical spectroscopy optimization algorithms particle swarm feature selection

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Joint calibration of Ensemble of Exemplar SVMs

Joint calibration of Ensemble of Exemplar SVMs

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IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Modolo, Davide Vezhnevets, Alexander Russakovsky, Olga Ferrari, Vittorio Univ Edinburgh Edinburgh EH8 9YL Midlothian Scotland Stanford Univ Stanford CA 94305 USA

ISBN: (纸本)9781467369640

We present a method for calibrating the Ensemble of Exemplar SVMs model. Unlike the standard approach, which calibrates each SVM independently, our method optimizes their joint performance as an ensemble. We formulate joint calibration as a constrained optimization problem and devise an efficient optimization algorithm to find its global optimum. The algorithm dynamically discards parts of the solution space that cannot contain the optimum early on, making the optimization computationally feasible. We experiment with EE-SVM trained on state-of-the-art CNN descriptors. Results on the ILSVRC 2014 and PASCAL VOC 2007 datasets show that (i) our joint calibration procedure outperforms independent calibration on the task of classifying windows as belonging to an object class or not;and (ii) this improved window classifier leads to better performance on the object detection task.

关键词： object class test sample Solution space Object detection Ensembles optimization algorithms jointing performance Joints Joints Calibration Constrained optimization windows windows

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Scalable and Distributed Submodular Maximization with Matroid Constraints 13

Scalable and Distributed Submodular Maximization with Matroi...

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13th International Symposium on Modeling and optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Clark, Andrew Alomair, Basel Bushnell, Linda Poovendran, Radha Worcester Polytech Inst Dept Elect & Comp Engn Worcester MA 01609 USA King Abdulaziz City Sci & Technol Natl Ctr Cybersecur Technol Riyadh Saudi Arabia Univ Washington Dept Elect Engn Seattle WA 98195 USA

ISBN: (纸本)9783901882746

Submodular maximization enables efficient approximation of machine learning, networking, and language processing problems. Typically, these problems have been shown to have matroid constraints, which generalize matching and partition conditions. Developing scalable, distributed submodular optimization algorithms that guarantee the same performance as centralized techniques has been an active area of research. In this paper, we address the problem of developing scalable distributed algorithms for submodular maximization with a matroid constraint. Our key step is to construct an auxiliary function from the submodular objective function, and develop distributed exchange-based algorithms for optimizing the auxiliary function. We first introduce a distributed algorithm for maximizing a submodular function with a matroid constraint. We then develop an algorithm for maximizing time-varying submodular functions under partition matroid constraints, which arises in sensor placement and data caching. We prove that both algorithms provide (1-1/e) optimality bounds, and hence achieve the same guarantees as the best centralized algorithms.

关键词： Scalability Matroid auxiliary function useful area distributed algorithms sensor placement optimization algorithms algorithms data cache Constraint

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