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Algebraic Statistics 2021年第2期12卷 115-124页

作者： Éva Czabarka László Székely Zoltán Toroczkai Shanise Walker Department of Mathematics University of South Carolina Columbia SC United States Visiting Professor Department of Pure and Applied Mathematics University of Johannesburg South Africa Department of Physics Department of Computer Science and Engineering University of Notre Dame IN United States Department of Mathematics University of Wisconsin-Eau Claire WI United States

The graphical realization of a given degree sequence and given partition adjacency matrix simultaneously, is a relevant problem in data driven modeling of networks. Here we formulate common generalizations of this problem and the exact matching problem, and solve them with an algebraic monte-carlo algorithm that runs in polynomial time if the number of partition classes is bounded by a constant. We note, that no deterministic polynomial time algorithm is known for any of these problems.

关键词： perfect matching exact matching degree sequence bipartite graph Hall's theorem joint degree matrix partition adjacency matrix monte-carlo algorithm computational complexity

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Parameter optimization of thermal network model for aerial cameras utilizing monte-carlo and genetic algorithm

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SCIENTIFIC REPORTS 2024年第1期14卷 1-18页

作者： Fan, Yue Feng, Wei Ren, Zhenxing Liu, Bingqi Huang, Long Wang, Dazhi Chengdu Univ Coll Mech Engn Chengdu 610106 Sichuan Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Sichuan Peoples R China

It is crucial to precisely calculate temperature utilizing thermal models, which require the determination of thermal parameters that optimally align model outcomes with experimental data. In many instances, the refinement of these models is undertaken within space instruments. This paper introduces an optimization methodology for thermal network models, with the objective of enhancing the accuracy of temperature predictions for aerial cameras. The investigation of internal convective heat transfer coefficients for both cylindrical and planar structures provides an estimation of convective thermal parameters. Based on the identification of thermally sensitive parameters and the reliability evaluation of transient temperature data through the monte-carlo simulation, the genetic algorithm is employed to search for global optimal parameter values that minimize the root mean square error (RMSE) between calculated and measured node temperatures. As a result, the optimized model shows significantly improved accuracy in temperature prediction, attaining an RMSE of 1.07 degrees C and reducing the maximum relative error between predicted and experimental results from 33.8 to 3.1%. Furthermore, the flight simulation and thermal control experiments validate the robustness of the optimized model, demonstrating that discrepancies between the observed and predicted temperatures are within 2 degrees C after re-correcting the external convection heat transfer coefficient value.

关键词： Aerial camera Thermal network model Parameter optimization monte-carlo algorithm Genetic algorithm

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Feasibility of monte-carlo algorithm in comparison with collapse-cone dose calculation algorithm of a commercial treatment planning system in the presence of high-density metallic implant: a dosimetric study

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JOURNAL OF THE EGYPTIAN NATIONAL CANCER INSTITUTE 2021年第1期33卷 2-2页

作者： Bhushan, Manindra Tripathi, Deepak Yadav, Girigesh Kumar, Lalit Chowdhary, Rahul Lal Pahuja, Anjali K. Suresh, Tamilarasu Shukla, Sushil Kumar Mitra, Swarupa Rajiv Gandhi Canc Inst & Res Ctr Div Med Phys Sect 5 New Delhi 110085 India Rajiv Gandhi Canc Inst & Res Ctr Dept Radiat Oncol Sect 5 New Delhi 110085 India Amity Univ AUUP Amity Sch Appl Sci Noida India Dr APJ Abdul Kalam Tech Univ Lucknow Uttar Pradesh India

Background The number of people with implanted hip prosthesis has grown worldwide. For radiotherapy planning of patients with hip implants, few main challenges are encountered. The aim of the present study was to evaluate the feasibility of different planning algorithms in the presence of high-density metallic implant in the treatment of patients with carcinoma cervix. Results It was found that D-98% were 44.49 +/- 0.11, 44.51 +/- 0.13, 44.39 +/- 0.22, and 44.45 +/- 0.16 Gy for 4FMC6MV (4-field technique calculated with monte-carlo algorithm and 6 MV photon energy), 4FMC6MV_WP (4-field technique calculated with monte-carlo algorithm and 6 MV photon energy without prosthesis), 4FCC6MV (4-field technique calculated with collapse-cone-convolution algorithm and 6 MV photon energy), and 4FCC6MV_WP (4-field technique calculated with collapse-cone-convolution algorithm and 6 MV photon energy without prosthesis) respectively. Similarly, D-2% were 49.40 +/- 0.84, 49.05 +/- 0.76, 48.97 +/- 0.91, and 48.57 +/- 0.85 Gray (Gy) for 4FMC6MV, 4FMC6MV_WP, 4FCC6MV, and 4FCC6MV_WP respectively. The present study has not suggested any major difference between the monte-carlo (MC) and collapse-cone-convolution (CCC) calculation algorithm in the presence of high-Z metallic implants. Volume of bowel receiving 15 Gy dose has shown a significant difference with prosthesis cases. This study investigates that hip prosthesis creates considerable changes in the treatment planning of cervical malignancies. Conclusion CCC algorithm is in good agreement with MC calculation algorithm in the presence of high-density metallic implants in terms of target coverage and avoidance organ sparing except few parameters.

关键词： Implant Collapse-cone-convolution Box technique monte-carlo algorithm Carcinoma cervix

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Exploiting the polyhedral geometry of stochastic linear bilevel programming

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MATHEMATICAL PROGRAMMING 2025年第1-2期210卷 695-730页

作者： Munoz, Gonzalo Salas, David Svensson, Anton Univ O Higgins Engn Sci Inst Rancagua Chile

We study linear bilevel programming problems whose lower-level objective is given by a random cost vector with known distribution. We consider the case where this distribution is nonatomic, allowing to reformulate the problem of the leader using the Bayesian approach in the sense of Salas and Svensson (SIAM J Optim 33(3):2311-2340, 2023), with a decision-dependent distribution that concentrates on the vertices of the feasible set of the follower's problem. We call this a vertex-supported belief. We prove that this formulation is piecewise affine over the so-called chamber complex of the feasible set of the high-point relaxation. We propose two algorithmic approaches to solve general problems enjoying this last property. The first one is based on enumerating the vertices of the chamber complex. This approach is not scalable, but we present it as a computational baseline and for its theoretical interest. The second one is a monte-carlo approximation scheme based on the fact that randomly drawn points of the domain lie, with probability 1, in the interior of full-dimensional chambers, where the problem (restricted to this chamber) can be reduced to a linear program. Finally, we evaluate these methods through computational experiments showing both approaches' advantages and challenges.

关键词： Bilevel programming Bayesian approach Chamber complex Enumeration algorithm monte-carlo algorithm

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Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

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COMPUTER PHYSICS COMMUNICATIONS 2025年 309卷

作者： Aehle, Max Novak, Mihaly Vassilev, Vassil Gauger, Nicolas R. Heinrich, Lukas Kagan, Michael Lange, David Univ Kaiserslautern Landau RPTU Gottlieb Daimler Str 42 D-67663 Kaiserslautern Germany European Org Nucl Res CERN Esplanade Particules 1 CH-1217 Geneva Switzerland Princeton Univ Dept Phys Jadwin HallWashington Rd Princeton NJ 08544 USA Tech Univ Munich Arcisstr 21 D-80333 Munich Germany SLAC Natl Accelerator Lab 2575 Sand Hill Rd Menlo Pk CA 94025 USA

Among the well-known methods to approximate derivatives of expectancies computed by monte-carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

关键词： Automatic differentiation Differentiable programming Gradient estimation monte-carlo algorithm High-energy physics Sampling calorimeter

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monte-carlo based random passive energy beamforming for reconfigurable intelligent surface assisted wireless power transfer

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Digital Communications and Networks 2023年第3期9卷 667-676页

作者： Ziyang Lu Yubin Zhao Xiaofan Li School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai519082China School of Intelligent System Science and Engineering Jinan UniversityZhuhai519070China

Reconfigurable intelligent surface(RIS)employs passive beamforming to control the wireless propagation channel,which benefits the wireless communication capacity and the received energy efficiency of wireless power transfer(WPT)*** beamforming schemes are classified as discrete and non-convex integer program-ming *** this paper,we propose a monte-carlo(MC)based random energy passive beamforming of RIS to achieve the maximum received power of electromagnetic(EM)WPT ***,the Gibbs sampling and re-sampling methods are employed to generate phase shift vector *** the sample with the maximum received power is considered the optimal *** order to adapt to the application scenarios,we develop two types of passive beamforming algorithms based on such MC sampling *** first passive beamforming uses an approximation of the integer programming as the initial sample,which is calculated based on the channel *** the second one is a purely randomized algorithm with the only total received power *** proposed methods present several advantages for RIS control,e.g.,fast convergence,easy implementation,robustness to the channel noise,and limited feedback requirement,and they are applicable even if the channel information is *** to the simulation results,our proposed methods outperform other approxi-mation and genetic *** our methods,the WPT system even significantly improves the power effi-ciency in the nonline-of-sight(NLOS)environment.

关键词： Reconfigurable intelligence surface Wireless power transfer monte-carlo algorithm Passive beamforming Gibbs sampling

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A probabilistic proof of the Perron-Frobenius theorem

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NAVAL RESEARCH LOGISTICS 2023年第5期70卷 443-453页

作者： Glynn, Peter W. Desai, Paritosh Y. Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA Target Corp Sunnyvale CA USA

The Perron-Frobenius theorem plays an important role in many areas of management science and operations research. This article provides a probabilistic perspective on the theorem, by discussing a proof that exploits a probabilistic representation of the Perron-Frobenius eigenvalue and eigenvectors in terms of the dynamics of a Markov chain. The proof recovers conditions in both the finite-dimensional and infinite-dimensional settings under which the Perron-Frobenius eigenvalue and eigenvectors have been shown to exist by other methods. In addition to providing new insights, the probabilistic representations that arise can be used to produce a monte-carlo algorithm for computing the Perron-Frobenius eigenvalue and eigenvectors that will be explored elsewhere.

关键词： Markov population decision monte-carlo algorithm Perron-Frobenius theorem

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Exploiting the Polyhedral Geometry of Stochastic Linear Bilevel Programming 24th

Exploiting the Polyhedral Geometry of Stochastic Linear Bile...

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24th International Conference on Integer Programming and Combinatorial Optimization (IPCO)

作者： Munoz, Gonzalo Salas, David Svensson, Anton Univ OHiggins Inst Ciencias Ingenierfa Rancagua Chile

ISBN: (纸本)9783031327254;9783031327261

We study linear bilevel programming problems whose lower-level objective is given by a random cost vector with known distribution. We consider the case where this distribution is nonatomic, allowing to pose the problem of the leader using vertex-supported beliefs in the sense of [29]. We prove that, under suitable assumptions, this formulation turns out to be piecewise affine over the so-called chamber complex of the feasible set of the high point relaxation. We propose two algorithmic approaches to solve general problems enjoying this last property. The first one is based on enumerating the vertices of the chamber complex. The second one is a monte-carlo approximation scheme based on the fact that randomly drawn points of the domain lie, with probability 1, in the interior of full-dimensional chambers, where the problem (restricted to this chamber) can be reduced to a linear program.

关键词： Bilevel Programming Bayesian Approach Chamber complex Enumeration algorithm monte-carlo algorithm

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Life cycle assessment and risk assessment of liquefied natural gas vehicles promotion

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2022年 153卷

作者： Sun, Shouheng Ertz, Myriam Univ Quebec Chicoutimi UQAC LaboNFC 555 Blvd Univ Chicoutimi PQ G7H 2B1 Canada

Liquefied natural gas (LNG) is gaining traction as a substitute energy source in the transportation sector. While presented as a promising energy alternative, LNG also faces criticism for being environmentally unsustainable. This debate has sparked interest from authorities, professionals, and business developers uncertain about the stance to take toward LNG. This study seeks to offer preliminary insights into this issue by investigating the environmental and economic impact of liquefied natural gas on heavy-duty vehicles (HDVs) in Canada. In this country, LNG sources are abundant. A thorough life cycle assessment is conducted on the environmental impact of deploying LNG as an alternative fuel for heavy-duty vehicles in the city of Saguenay, Canada. In particular, an extensive risk assessment is also carried out on the impact of uncertain factors such as policies and markets on the economic benefits of stakeholders by using the monte-carlo algorithm. Although the project was eventually canceled in Saguenay and implemented by LNG Canada in Kitimat, British Columbia, Canada, the results show that promoting LNG in Saguenay may yield significant environmental benefits on almost all environmental impact categories, even in the worst possible development scenario. However, it should be noted that the engine's methane emission and energy efficiency both significantly influence LNG's global warming potential. Advances in technology will show more significant potential for environmental preservation. Additionally, appropriate incentives can significantly increase the economic benefits and reduce the investment risk of facilities and vehicles.

关键词： Liquefied natural gas Life cycle assessment Risk assessment Environmental impact Climate change monte-carlo algorithm

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Revealing the theoretical assumptions of the trap-depth distribution model in the thermoluminescence theory

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THIN SOLID FILMS 2020年 714卷 138390-138390页

作者： Sadek, A. M. Natl Inst Stand NIS Ionizing Radiat Metrol Dept PO 136 Giza 12211 Egypt

The theoretical assumptions of the analytical expressions characterizing the thermoluminescence glow-peak arising from a continuous trap-depth distribution have been investigated. The sets of the differential equations governing the electrons' transitions within a continuous trap-depth distribution during the irradiation and heating stages have been numerically solved. The analytical expressions are essentially based on a theoretical assumption that correlates the concentrations of the trapped electrons with the distribution of the trap depths in the bandgap. This correlation could not be considered in the numerical solution, since the irradiation stage is entirely independent of the trap depth. Thus, the final values of the instantaneous trap-filling functions of the irradiation stage do not depend on the trap depth, but rather on the trap capacity and the trapping probability coefficient. Consequently, in the numerical solution, the distribution of the trap depths and the distribution of the trapped electrons are independent. This inconsistency between the numerical solution and the analytical expression has led to differences in the shape of the thermoluminescence glow peaks resulting from the same trap-depth spectrum.

关键词： Trap-depth distribution Thermoluminescence models monte-carlo algorithm

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