检索结果-内蒙古大学图书馆

AIAA SciTech Forum

作者： Parish, Eric J. Geraci, Gianluca Krath, Elizabeth Blonigan, Patrick Sandia Natl Labs Computat Data Sci Livermore CA 94550 USA Sandia Natl Labs Optimizat & Uncertainty Quantificat Albuquerque NM USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This work investigates the use of the reduced-basis method for multifidelity uncertainty quantification (UQ) with application to the Reynolds-Averaged Navier-Stokes equations. We examine the use of a greedy algorithm that leverages easily computable error estimates for constructing a reduced basis. This reduced basis is used to define a Galerkin reduced-order model that leverages entropy-variable transforms to maintain robustness. We embed our reduced-order model within sampling multifidelity UQ methods and assess its utility for more-efficiently propagating parametric uncertainties with the Spalart-Allmaras turbulence model. Results are presented on several hypersonic turbulent flow configurations.

关键词： Reynolds Averaged Navier Stokes Uncertainty Quantification greedy algorithm Entropy Flow Conditions Spalart Allmaras Turbulence Model Stress Distribution Finite Volume Method Direct Numerical Simulation Turbulent Boundary Layer

来源：评论

学校读者我要写书评

暂无评论

An uncertain sustainable supply chain network design for regulating greenhouse gas emission and supply chain cost

引用

CLEANER LOGISTICS AND SUPPLY CHAIN 2024年 10卷

作者： Kumar, Amit Kumar, Kaushal Univ Delhi Fac Math Sci Dept Operat Res Delhi India

The increasing global concern for sustainability in supply chain management is driven by stricter government regulations addressing environmental pollution and social injustice. This has led to a growing emphasis on integrating sustainability into supply chain practices. However, there is limited research on incorporating all three dimensions of sustainability (economic, environmental, and social) into supply chain management. This study presents a mixed-integer linear programming model for designing an uncertain supply chain network design that aims to minimize overall costs (establishment, production, and transportation/routing costs) while considering carbon emissions and a few social factors simultaneously. The study considers sustainable aspects of decision-making process and utilizes chance-constrained programming to address uncertainties. The proposed model attempts to maintain balanced flow levels across all stages of the network, optimizing the utilization of raw materials and production. The proposed optimization model is a cost minimization model that also tries to minimize greenhouse gas emissions throughout the entire network. A greedy based heuristic is provided for dealing with larger instances of the given decision making problem. Additionally, sensitivity analysis has also been carried out to explore the impact of various parameters involved.

关键词： Sustainable supply chain management Supply chain network design Greenhouse gas emission Chance -constrained programming Mixed integer linear programming greedy algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimization Approaches for the Optimal Placement of Electrical Charging Stations 20

Optimization Approaches for the Optimal Placement of Electri...

引用

20th IEEE International Wireless Communications and Mobile Computing (IEEE IWCMC) - Green and Intelligent Communications

作者： Mejjaouli, Sobhi Alnourani, Sanabel Almobarek, Malek Guizani, Sghaier Alfaisal Univ Coll Engn Riyadh Saudi Arabia Univ Strathclyde Glasgow Lanark Scotland

ISBN: (纸本)9798350361261;9798350361278

Transportation electrification is among the vital solutions for green transport environments. Since the number of electric cars has been increasing, a fast deployment of electric charging stations is needed. However, charging infrastructure costs can be very high, especially if super-fast chargers (level 3) need to be deployed. Moreover, charging stations cannot be installed everywhere due to their high energy consumption. In this context, we herein propose two optimization solutions to solve an assignment problem for a fleet of battery-electric cars and existing points of interest (or stations). The first solution is based on the greedy algorithm (GA) approach, while the second solution is based on linear programming (LP). Different constraints were considered, such as the number of charging stations, maximum capacity of charging stations, final battery state, waiting time, driving style, distance to each station, and charging cost. An illustrative example was used to demonstrate how using a cost function of level 3 chargers coupled with charging costs seriously affects the deployment cost and charging location. The chargers' installation cost, charging stations' cost, the maximum number of charging points, the number of charging stations, the final state of charge, and drivers' different road behaviors were considered in the design of both models. Moreover, a new cost function was injected into the models to determine each battery-electric (BE) car assignment. Using the proposed algorithm, we considered high charging demands for BE cars when reaching their destinations without violating their energy needs.

关键词： Electric cars charging stations optimization assignment problem linear programming greedy algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal Predictive Guidance for Autonomous Hazard Detection and Avoidance

Optimal Predictive Guidance for Autonomous Hazard Detection ...

引用

AIAA SciTech Forum

作者： Tomita, Kento Shimane, Yuri Ho, Koki Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Space Syst Optimizat Grp Space Syst Design Lab 620 Chery St NW Atlanta GA 30332 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper formulates the guidance optimization problem for autonomous hazard detection and avoidance (HD&A) for planetary landing. With the physically limited accuracy of terrain sensing and associated uncertainty, future observation and trajectory must be optimized to maximize the probability of safe landing. We propose two reachability-based guidance algorithms based on different approximations. The inner-loop optimization for the reachability computation is bypassed with a neural network-based reachable set evaluator. The numerical experiments with simulated Mars landing scenarios are presented.

关键词： Guidance algorithms Space Missions Neural Networks Planetary Landing greedy algorithm Trajectory Optimization Powered Descent Guidance Convex Optimization Open Loop Markov Decision Process

来源：评论

学校读者我要写书评

暂无评论

greedy selection of sensors with measurements under correlated noise

引用

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2024年第1期2024卷 31页

作者： Kim, Yoon Hak Chosun Univ Coll IT Convergence Engn Dept Elect Engn 309 Pilmun Daero Gwangju 61452 South Korea

We address the sensor selection problem where linear measurements under correlated noise are gathered at the selected nodes to estimate the unknown parameter. Since finding the best subset of sensor nodes that minimizes the estimation error requires a prohibitive computational cost especially for a large number of nodes, we propose a greedy selection algorithm that uses the log-determinant of the inverse estimation error covariance matrix as the metric to be maximized. We further manipulate the metric by employing the QR and LU factorizations to derive a simple analytic rule which enables an efficient selection of one node at each iteration in a greedy manner. We also make a complexity analysis of the proposed algorithm and compare with different selection methods, leading to a competitive complexity of the proposed algorithm. For performance evaluation, we conduct numerical experiments using randomly generated measurements under correlated noise and demonstrate that the proposed algorithm achieves a good estimation accuracy with a reasonable selection complexity as compared with the previous novel selection methods.

关键词： Sensor selection greedy algorithm QR factorization LU factorization Correlated noise

来源：评论

学校读者我要写书评

暂无评论

Simulating Functioning of Decision Trees for Tasks on Decision Rule Systems

Simulating Functioning of Decision Trees for Tasks on Decisi...

引用

International Joint Conference on Rough Sets (IJCRS)

作者： Durdymyradov, Kerven Moshkov, Mikhail King Abdullah Univ Sci & Technol KAUST Comp Elect & Math Sci & Engn Div Thuwal 239556900 Saudi Arabia King Abdullah Univ Sci & Technol KAUST Computat Biosci Res Ctr Thuwal 239556900 Saudi Arabia

ISBN: (纸本)9783031656644;9783031656651

DRSs (Decision Rule Systems) and DTs (Decision Trees) are well known as classification tools, knowledge representation methods, and algorithms. Their clarity and ease of interpretation in data analysis are widely recognized. The study of the relationship between DTs and DRSs is an important problem in computer science. There are established methods for converting DTs to DRSs. In this work, we explore the inverse transformation problem, which is challenging. Rather than constructing a full DT that answers the tasks on DRSs, our research provides a greedy algorithm that simulates the functioning of a DT for an input array of feature values.

关键词： Decision trees Decision rule systems greedy algorithm

来源：评论

学校读者我要写书评

暂无评论

EMGA: An Evolutionary Memory Grouping algorithm for MBIST

EMGA: An Evolutionary Memory Grouping Algorithm for MBIST

引用

2nd International Symposium of Electronics Design Automation (ISEDA)

作者： Li, Yang Duan, Yongqiang Zhang, Hao Niu, Dan Wu, Xiao Jin, Zhou China Univ Petr Super Sci Software Lab Beijing Peoples R China Southeast Univ Sch Automat Nanjing Peoples R China Huada Empyrean Software Co Ltd Beijing Peoples R China

ISBN: (纸本)9798350352047;9798350352030

MBIST (Memory Built-In Self-Test) is a widely used methodology in chip design and fabrication to detect and localize faults in memories. Due to the large memory sizes of modern chips, memories need to be grouped in order to manage and test them efficiently. However, the time complexity of the direct solution is high due to the large number of constraints. In addition, the size of the memories is large and the grouping quality obtained directly using the heuristic algorithm is poor. In this paper, we propose a heuristic-based MBIST grouping algorithm to maintain high efficiency while achieving high quality grouping. We employ a multi-stage steps. We firstly divide the numerous constraints into two categories to reduce the constraint dimensions and obtain an initial grouping result. We then use a greedy algorithm with a penalty term to quickly obtain the result that satisfies all the constraints from the initial result in order to reduce the time consumption and the size of the grouping. In order to avoid local optimal solutions, we further use an improved genetic algorithm to optimize the result of the greedy algorithm to obtain higher quality groupings. The experimental results demonstrate that our algorithm reduces the number of groups 119.44% on average compared with the K-Means method. Compared with simulated annealing algorithm and genetic algorithm, EMGA reduces the number of groups by 8.35% and 4.66%, and time by 79.51% and 73.30%, respectively.

关键词： MBIST grouping greedy algorithm genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An Efficient algorithm for Decomposing a Vector into Two Vectors with a Small Uniform Norm

引用

MATHEMATICAL NOTES 2023年第5-6期114卷 1484-1487页

作者： Kashin, B. S. Romskii, D. G. Lomonosov Moscow State Univ Moscow 119991 Russia

来源：评论

学校读者我要写书评

暂无评论

Uniformly distributed sequences generated by a greedy minimization of the L₂ discrepancy

引用

Moscow Journal of Combinatorics and Number Theory 2022年第3期11卷 215-236页

作者： Kritzinger, Ralph Steyr Austria

The aim of this paper is to develop greedy algorithms which generate uniformly distributed sequences in the d-dimensional unit cube [0, 1]d . The figures of merit are three different variants of the L2 discrepancy. Th... 详细信息

The aim of this paper is to develop greedy algorithms which generate uniformly distributed sequences in the d-dimensional unit cube [0, 1]^d . The figures of merit are three different variants of the L₂ discrepancy. Theoretical results along with numerical experiments suggest that the resulting sequences have excellent distribution properties. The approach we follow here is motivated by recent work of Steinerberger and Pausinger who consider similar greedy algorithms, where they minimize functionals that can be related to the star discrepancy or energy of point sets. In contrast to many greedy algorithms, where the resulting elements of the sequence can only be given numerically, we will find that in the one-dimensional case our algorithms yield rational numbers which we can describe precisely. In particular, we will observe that any initial segment of a sequence in [0, 1) can be naturally extended to a uniformly distributed sequence where all subsequent elements are of the form x_N = (2n − 1)/(2N) for some n ∈ {1, …, N}. We will also investigate the dependence of the L₂ discrepancy of the resulting sequences on the dimension d. © 2022, Mathematical Sciences Publishers. All rights reserved.

关键词： diaphony greedy algorithm L2 discrepancy uniform distribution modulo 1 van der Corput sequence

来源：评论

学校读者我要写书评

暂无评论

Minimum-Cost Routing of two UAVs with Communication Constraints

Minimum-Cost Routing of two UAVs with Communication Constrai...

引用

AIAA SciTech Forum

作者： Moorthy, Karthik Kumar, Deepak Prakash Darbha, Swaroop Bihl, Trevor Rathinam, Sivakumar Texas A&M Univ Mech Engn 3123 TAMU College Stn TX 77843 USA Air Force Res Lab Sensing Management Branch Dayton OH 45433 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper proposes a formulation to determine the routes of two unmanned aerial vehicles (UAVs) traveling in lockstep fashion, maintaining within a specified proximity of one another, to cooperatively cover all targets in minimum time. The results of this study provide a framework for UAV mission planning or other applications where multiple UAVs are required to travel synchronously to visit a given set of targets while keeping within a distance of one another to maintain communication. A Mixed Integer Linear Program (MILP) is formulated to determine this minimum cost tour for both UAVs. This MILP is computationally expensive to solve which makes it impractical to obtain solutions as the problem size scales up. Therefore, a local search heuristic was formulated to approximate the optimal solutions in a quicker manner. The quality of the heuristic was measured by comparing its solutions against those from a linear programming model (LP) serving as a lower bound to the optimal solution. To observe the relationship between the problem size and the heuristic solution quality, randomly generated instances of.. = 20 to.. = 100 targets were simulated in 32.. by 32.. unit grids, varying the proximity limit from 15-30 units. It was found that the heuristic consistently delivered higher-quality solutions when smaller UAV proximity value requirements were imposed. Specifically, the heuristic solutions deviated 23-35% from the LP solutions when the proximity limit imposed was 15 units.

关键词： Unmanned Aerial Vehicle Mixed Integer Linear Programming Linear Programming Python Robots Aerospace Engineering Heuristic Approach Military Operations Search algorithm greedy algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：