检索结果-内蒙古大学图书馆

10th International Conference on Evolutionary multi-Criterion optimization, EMO 2019

作者： Powell, Courtney Miura, Katsunori Munetomo, Masaharu Hokkaido University Sapporo060–0811 Japan Otaru University of Commerce Otaru047–8501 Japan

ISBN: (纸本)9783030125974

This paper presents and evaluates a constrained multi-objective optimization method for scientific workflow resource selection that uses equivalent transformation for constraint handling. Two different approaches are compared using a case study of optimal cloud resource configuration selection for a practical genomic analytics workflow. In the first approach, called the nondominated sorting equivalent transformation (NSET) method, feasible configurations are generated via equivalent transformation and the Pareto-optimal configurations are selected from among them via a process of nondominated sorting, reference points association, and niching/elitism. In the second approach, Pareto-optimal configurations are generated via the nondominated sorting genetic algorithms II/III (NSGA-II/III) and feasible configurations are generated via equivalent transformation. Then, the configurations that are common to both processes are considered to be both feasible and optimal. Preliminary results based on the Pareto-optimal configuration sets generated by NSGA-II/III indicate that NSET is feasible for constrained multi-objective optimization of practical scientific workflow resource selection problems. © Springer Nature Switzerland AG 2019.

关键词： Genome

来源：评论

学校读者我要写书评

暂无评论

Accelerated Inference in Markov Random Fields via Smooth Riemannian optimization

引用

IEEE ROBOTICS AND AUTOMATION LETTERS 2019年第2期4卷 1295-1302页

作者： Hu, Siyi Carlone, Luca MIT Informat & Decis Syst Lab Cambridge MA 02139 USA

Markov random fields (MRFs) are a popular model for several pattern recognition and reconstruction problems in robotics and computer vision. Inference in MRFs is intractable in general and related work resorts to approximation algorithms. Among those techniques, semidefinite programming (SDP) relaxations have been shown to provide accurate estimates, while scaling poorly with the problem size and being typically slow for practical applications. Our first contribution is to design a dual ascent method to solve standard SDP relaxations that takes advantage of the geometric structure of the problem to speed up computation. This technique, named dual ascent Riemannian staircase (DARS), is able to solve large problem instances in seconds. Our second contribution is to develop a second and faster approach. The backbone of this second approach is a novel SDP relaxation combined with a fast and scalable solver based on smooth Riemannian optimization. We show that this approach, named Fast Unconstrained SEmidefinite Solver (FUSES), can solve large problems in milliseconds. Contrarily to local MRF solvers, e.g., loopy belief propagation, our approaches do not require an initial guess. Moreover, we leverage recent results from optimization theory to provide per-instance sub-optimality guarantees. We demonstrate the proposed approaches in multi-class image segmentation problems. Extensive experimental evidence shows that: 1) FUSES and DARS produce near-optimal solutions, attaining an objective within 0.1% of the optimum;2) FUSES and DARS are remarkably faster than general-purpose SDP solvers, and FUSES is more than two orders of magnitude faster than DARS while attaining similar solution quality;and 3) FUSES is faster than local search methods while being a global solver.

关键词： Object detection segmentation and categorization optimization and optimal control recognition

来源：评论

学校读者我要写书评

暂无评论

Constraining counterexamples in Hybrid system Falsification: penalty-based approaches

arXiv

引用

arXiv 2020年

作者： Zhang, Zhenya Arcaini, Paolo Hasuo, Ichiro National Institute of Informatics Tokyo Japan Hayama Japan

Falsification of hybrid systems is attracting ever-growing attention in quality assurance of Cyber-Physical Systems (CPS) as a practical alternative to exhaustive formal verification. In falsification, one searches for a falsifying input that drives a given black-box model to output an undesired signal. In this paper, we identify input constraints—such as the constraint "the throttle and brake pedals should not pressed simultaneously" for an automotive powertrain model—as a key factor for the practical value of falsification methods. We propose three approaches for systematically addressing input constraints in optimization-based falsification, two among which come from the lexicographic method studied in the context of constrained multi-objective optimization. Our experiments show the approaches’ effectiveness. Copyright © 2020, The Authors. All rights reserved.

关键词： Hybrid systems

来源：评论

学校读者我要写书评

暂无评论

Qualitative and quantitative analysis of the dietary approaches to stop hypertension diet for personalized hypertension management

引用

Computers & Industrial Engineering 2025年 207卷

作者： Chun-Wei Chiu Thi-Phuong-Thanh Le Chien-Hsiung Huang Ching-Ter Chang Chao-Chun Cheng Graduate Institute of Management Chang Gung University No.259 Wenhua 1st Rd. Guishan Dist. Taoyuan City 333323 Taiwan (ROC) Faculty of Business Administration Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Emergency Medicine Chang Gung Memorial Hospital Linkou and College of Medicine Chang Gung University No.15 Wenhua 1st Rd. Guishan Dist. Taoyuan City 333011 Taiwan (ROC) Department of Industrial Engineering and Management Ming Chi University of Technology No.84 Gungjuan Rd. Taishan Dist. New Taipei City 243303 Taiwan (ROC) Department of Nutrition and Health Sciences Chang Gung University of Science and Technology No.261 Wenhua 1st Rd. Guishan Dist. Taoyuan City 333323 Taiwan (ROC)

Hypertension is a major global health concern, yet personalized planning for diet and lifestyle remains a challenge in clinical practice. To address this issue, this study proposes a novel Personal Health Support Model (PHSM) based on the principle of the dietary approaches to stop hypertension (DASH) diet, aiming to improve the precision and adaptability of personalized recommendations. It integrates the analytic hierarchy process (AHP), fuzzy multi-choice goal programming (FMCGP), and nonlinear multi-segment goal programming (NLMSGP) to construct a comprehensive multi-criteria decision-support framework that considers individual characteristics, dietary preferences, and clinical guidelines. The main contributions of this study are as follows: 1. PHSM calculates daily calorie and nutrient requirements based on gender, age, and activity level to ensure dietary plans align with individual needs. 2. PHSM provides a personalized exercise plans tailored to individual health conditions and lifestyle preferences to support blood pressure management and overall well-being. 3. Utilizing FMCGP techniques to accommodate diverse dietary and lifestyle preferences, offering precise personalized blood pressure management solutions. 4. Introducing the NLMSGP approach addresses non-scalar coefficient issues, optimizing dietary plans by considering the timing and quantify of food intake. The study results indicate that PHSM significantly outperforms conventional dietitian-led approaches in term of user satisfaction, engagement, and perceived effectiveness. Its structured design and real-time optimization features are also associated with stronger behavioral intention and adherence. In conclusion, this PHSM shows strong potential for clinical applications and can be integrated with AI-driven health platforms, contributing to both the practical advancement of intelligent dietary planning and the theoretical development of multi-objective health decision-making.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hybrid Adaptive Evolutionary algorithm for multi-objective optimization

arXiv

引用

arXiv 2020年

作者： Prieto, Jeisson Gomez, Jonatan Universidad Nacional de Colombia Facultad de Ciencias Departamento de Matemáticas Bogotá Colombia Universidad Nacional de Colombia Facultad de Ingeniería Dpto. Ing. Sistemas e Industrial Bogotá Colombia

The major difficulty in multi-objective optimization Evolutionary Algorithms (MOEAs) is how to find an appropriate solution that is able to converge towards the true Pareto Front with high diversity. Most existing methodologies, which have demonstrated their niche on various practical problems involving two and three objectives, face significant challenges in the dependency of the selection of the EA parameters. Moreover, the process of setting such parameters is considered time-consuming, and several research works have tried to deal with this problem. This paper proposed a new multi-objective Algorithm as an extension of the Hybrid Adaptive Evolutionary algorithm (HAEA) called MoHAEA. MoHAEA allows dynamic adaptation of the application of operator probabilities (rates) to evolve with the solution of the multi-objective problems combining the dominance- and decomposition-based approaches. MoHAEA is compared with four states of the art MOEAs, namely MOEA/D, paλ-MOEA/D, MOEA/D-AWA, and NSGA-II on ten widely used multi-objective test problems. Experimental results indicate that MoHAEA outperforms the benchmark algorithms in terms of how it is able to find a well-covered and well-distributed set of points on the Pareto Front. Copyright © 2020, The Authors. All rights reserved.

关键词： multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Reliability-based robust design optimization of polymer nanocomposites to enhance percolated electrical conductivity considering correlated input variables using multivariate distributions

引用

POLYMER 2020年 186卷

作者： Doh, Jaehyeok Yang, Qing Raghavan, Nagarajan SUTD Engn Prod Dev EPD Pillar Singapore 487372 Singapore Zhejiang Univ Coll Opt Sci & Engn State Key Lab Modern Opt Instrumentat Hangzhou 310027 Peoples R China

In this study, reliability-based robust design optimization (RBRDO) for polymer nanocomposites (PNCs) design is conducted to secure the reliability of design conditions concerning the electrical percolation threshold and carbon nanotube (CNT) aspect ratio as well as the robustness for electrical conductivity. CNT diameter and length are known as following the lognormal and Weibull distributions respectively. To reflect the different probability distributions of CNT geometry parameters and correlations between these random input variables, Nataf transformation is employed. By performing several case studies with the first-order reliability method (FORM)-based RBRDO approaches, the objective function exhibited a noteworthy change according to the correlation coefficients and the reliability and robustness for PNCs were satisfied concurrently. Furthermore, the highlight of this work is to provide a generic framework for practical PNC design and multi-objective optimization to enhance electrical performance efficiently.

关键词： Polymer nanocomposites (PNCs) Electrical percolation threshold Reliability-based robust design optimization (RBRDO)

来源：评论

学校读者我要写书评

暂无评论

社区绿地空间绩效测度方法优化研究--基于供需双向关系的空间模拟分析

引用

南方建筑 2023年第10期 47-58页

作者：刘泽邱宁宁北京工业大学城市建设学部

社区绿地空间绩效是衡量社区绿地配置合理程度的重要指标。其传统测度方法多沿用城市宏观尺度下的评测内容,故难以突出社区尺度差异化的绩效内涵。针对此问题,提出融入多智能体模拟的空间绩效测度方法。首先基于对供需两端个体特征的观... 详细信息

社区绿地空间绩效是衡量社区绿地配置合理程度的重要指标。其传统测度方法多沿用城市宏观尺度下的评测内容,故难以突出社区尺度差异化的绩效内涵。针对此问题,提出融入多智能体模拟的空间绩效测度方法。首先基于对供需两端个体特征的观测分析,在网络模型中引入居民选择概率、绿地吸引力等参数;其次融合居民空间决策行为的仿真模拟构建绿地空间绩效精细化评测模型,实现供需双向关系对绩效测度的有效反馈;最后以北京3个社区为例进行实证检验。结果表明优化模型较传统测度方法,在社区绿地空间绩效评测的精度方面有显著提升效果。

关键词：社区绿地空间绩效供需双向关系空间模型

来源：评论

学校读者我要写书评

暂无评论

Genetic-algorithm-based approaches for enhancing fairness and efficiency in dynamic airport slot allocation

引用

Chinese Journal of Aeronautics 2025年

作者： Ruoshi YANG Zhiqiang FENG Meilong LE Hongyan ZHANG Ji MA Department of Aerodynamics Nanjing Aeronautical Institute Nanjing 210016 China School of Information Science and Technology Hainan Normal University Haikou 571158 China Sino-European Institute of Aviation Engineering (SIAE) Civil Aviation University of China Tianjin 300300 China

Airports around the world commonly face challenges in managing airport slot allocation. Effective management of limited slot resources by civil aviation authority often requires redistributing requested slots among airlines. The allocation process must operate within the prescribed capacity limits of the airport while adhering to established priorities and regulations. Additionally, ensuring market fairness is a key objective, as the value of airport slots plays a significant role in the adjustment process. This transforms the traditional time-shift-based problem into a complex multi-objective optimization problem. Addressing such complications is of significant importance to airlines, airports, and passengers alike. Due to the complexity of fairness metrics, traditional integer programming models encounter difficulties in finding effective solutions. This study proposes a neighborhood search strategy to tackle the single airport slot allocation, making it adaptable to both static and rolling capacity scenarios. Two Genetic Algorithms(GAs) are introduced, corresponding to time adjustment and sequence adjustment strategies, respectively. The GA based on the time adjustment strategy demonstrates high robustness, while the sequence adjustment strategy builds upon this GA to develop a simple heuristic algorithm that offers rapid convergence. Case studies conducted at seven airports in China confirm that all three algorithms yield high-quality adjustment solutions suitable for the majority of applications. Further, Pareto analysis reveals that these algorithms effectively balance the adjustment shifts and fairness metrics, demonstrating high practical value and broad applicability.

关键词： Air traffic management Airport slot allocation Genetic algorithm Neighborhood search Rolling horizon

来源：评论

学校读者我要写书评

暂无评论

A Framework for Optimum Determination of LCL-Filter Parameters for N-Level Voltage Source Inverters Using Heuristic Approach

引用

IEEE ACCESS 2020年 8卷 209212-209223页

作者： Alamri, Basem Alharbi, Yasser Mohammed Taif Univ Coll Engn Dept Elect Engn At Taif 21944 Saudi Arabia

The use of voltage source multilevel inverters (VS-MLIs) has grown enormously over the last decade, and it is expected that these inverters will be deployed in future power grids (smart grids), especially for medium voltage-high power applications. This paper investigates the application of passive power filters (PPFs) for harmonic mitigation at the output of VS-MLIs for more efficient grid integration of renewable energy sources. It proposes a generic model, using a heuristic approach, for the optimum design of an LCL power filter at the output of VS-MLIs. The proposed model transforms the LCL filter design problem into an optimization problem and applies a genetic algorithm (GA) to solve it. The objective function to be optimized is a multi-objective function based on inverters' total harmonic distortion and energy losses. The optimization problem is subject to applied design constraints. As a main optimization objective, a precise evaluation methodology for the inverter power losses is presented, which was built according to a practical switching device datasheet. The method is applicable to any VS-MLI topology and any number of levels (N). As a case study, the proposed design optimization approach was implemented to optimally design the LCL filter at the output of a grid connected 11 KV, 5 MVA 7-level cascaded H-bridge multilevel invert (CHB-MLI). The IGBT module Device IGBT of type FZ400R65KE3 by Infineon was used for simulation. MATLAB-SIMULINK is used for the modelling and simulation. We found that the proposed design approach is more generic, efficient, and simple to apply than conventional design approaches which requires more system detail, relies more on the designer's experience, and normally does not results in optimum design. The proposed approach is generic and can be applied for different VS-MLIs topologies and for any number of levels (N).

关键词： Switches Power harmonic filters Harmonic analysis Topology optimization Mathematical model Insulated gate bipolar transistors DC AC inverters LCL filter power quality genetic algorithm multilevel inverter renewable energy power conversion grid integration

来源：评论

学校读者我要写书评

暂无评论

PREEMPT: Scalable Epidemic Interventions Using Submodular optimization on multi-GPU Systems

PREEMPT: Scalable Epidemic Interventions Using Submodular Op...

引用

International Conference on High Performance Computing, Networking, Storage and Analysis (SC)

作者： Minutoli, Marco Sambaturu, Prathyush Halappanavar, Mahantesh Tumeo, Antonino Kalyananaraman, Ananth Vullikanti, Anil Pacific Northwest Natl Lab Richland WA 99352 USA Univ Virginia Charlottesville VA USA Washington State Univ Pullman WA 99164 USA

ISBN: (纸本)9781728199986

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we present PREEMPT, a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for PREEMPT, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that PREEMPT is able to achieve a significant reduction (up to 6.75x) in the percentage of people infected and up to 98% reduction in the peak of the infection on a city scale network. We also show strong scaling results of PREEMPT on up to 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its -kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

关键词： Epidemic networks vaccination submodular influence maximization CPU-GPU parallel algorithms.

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：