检索结果-内蒙古大学图书馆

20th International Conference on Network and Service Management

作者： Di Cicco, Nicola Poltronieri, Filippo Santos, Jose Zaccarini, Mattia Tortonesi, Mauro Stefanelli, Cesare de Turck, Filip Politecn Milan Dept Elect Informat & Bioengn DEIB Milan Italy Univ Ferrara Distributed Syst Res Grp Ferrara Italy Univ Ghent IMEC IDLab Dept Informat Technol Ghent Belgium

ISBN: (纸本)9798331505158;9783903176669

Orchestrating microservice applications deployed on a federation of globally distributed Kubernetes clusters is a challenging and multifaceted optimization problem. It is not only computationally hard, but also requires balancing a delicate trade-off between competing performance metrics, such as latency, deployment cost, and service interruption frequency. Classical approaches in the literature merge multiple objectives into a single one via, e.g., linear combinations. However, in practice, it is complex to express a priori a quantitative preference between heterogeneous objectives, let alone with simple linear combinations. This paper adopts a more comprehensive approach leveraging proper multi-objective optimization (MOO), with the goal of producing multiple solutions from the Pareto Front. (PF). Therefore, the orchestrator can inspect a posteriori all possible "optimal" trade-offs and decide on the strategy that best tits their operating requirements. To solve the MOO problem, this paper adopts state-of-the-art multi-objective Evolutionary Algorithms and shows their effectiveness in solving the MOO problem. Illustrative results highlight the practical benefits of a MOO formulation, providing several tens of nondominated solutions and evenly covering the objectives' space.

关键词： Kubernetes Resource Allocation multi objective optimization ILP Evolutionary Algorithms Compute Continuum

来源：评论

学校读者我要写书评

暂无评论

Chaos-enhanced multi-objective tunicate swarm algorithm for economic-emission load dispatch problem

引用

SOFT COMPUTING 2023年第9期27卷 5721-5739页

作者： Rizk-Allah, Rizk M. Hagag, Enas A. El-Fergany, Attia A. Menoufia Univ Fac Engn Basic Engn Sci Dept Shibin Al Kawm 32511 Egypt Zagazig Univ Fac Engn Elect Power & Machines Dept Zagazig 44519 Egypt

Climate change and environmental protection have a significant impact on thermal plants. So, the main principles of combined economic-emission dispatch (CEED) problem are indeed to reduce greenhouse gas emissions and fuel costs. Many approaches have demonstrated their efficacy in addressing CEED problem. However, designing a robust algorithm capable of achieving the Pareto optimal solutions under its multimodality and non-convexity natures caused by valve ripple effects is a true challenge. In this paper, chaos-enhanced multi-objective tunicate swarm algorithm (CMOTSA) for CEED problem. To promote the exploration and exploitation abilities of the basic tunicate swarm algorithm (TSA), an exponential strategy based on chaotic logistic map (ESCL) is incorporated. Based on ESCL in CMOTSA, it can improve the possibility of diversification feature to search different areas within the solution space, and then, gradually with the progress of iterative process it converts to emphasize the intensification ability. The efficacy of CMOTSA is approved by applying it to some of multi-objective benchmarking functions which have different Pareto front characteristics including convex, discrete, and non-convex. The inverted generational distance (IGD) and generational distance (GD) are employed to assess the robustness and the good quality of CMOTSA against some successful algorithms. Additionally, the computational time is evaluated, the CMOTSA consumes less time for most functions. The CMOTSA is applied to one of the practical engineering problems such as combined economic and emission dispatch (CEED) with including the valve ripples. By using three different systems (IEEE 30-bus with 6 generators system, 10 units system and IEEE 118-bus with 14 generating units), the methodology validation is made. It can be stated for the large-scale case of 118-bus systems that the results of the CMOTSA are equal to 8741.3 $/h for the minimum cost and 2747.6 ton/h for the minimum emission which

关键词： multi-objective optimization Chaos maps Chaotic multi-objective tunicate swarm algorithm Combined economic and emission dispatch Valve-point effects

来源：评论

学校读者我要写书评

暂无评论

Pareto Front Analysis Method for optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime

引用

CSEE Journal of Power and Energy Systems 2023年第1期9卷 111-121页

作者： Qingmian Chai Cuo Zhang Yan Xu Zhao Yang Dong Rui Zhang School of Electrical Engineering and Telecommunications The University of New South WalesSydneyNSW 2052Australia School of Electrical and Information Engineering The University of SydneySydneyNSW 2006Australia School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore

Photovoltaic(PV)inverter-based volt/var control(VVC)is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV ***,PV inverter operational reliability has arisen as a critical concern for practical VVC *** paper proposes a new PV inverter based VVC optimization model and a Pareto front analysis method for maintaining a satisfactory inverter ***,reliability of the vulnerable DC-link capacitor inside a PV inverter is analyzed,and long-term VVC impact on inverter operational reliability is ***,a multi-objective PV inverter based VVC optimization model is proposed for minimizing both inverter apparent power output and network power loss with a weighting ***,a Pareto front analysis method is developed to visualize the impact of the weighting factor on VVC performance and inverter reliability,thus determining the effective weighting factor to reduce network power loss with expected inverter *** of the proposed VVC optimization model and Pareto front analysis method are verified in a case study.

关键词： Distribution network inverter reliability analysis pareto front analysis photovoltaic stochastic optimization volt/var control

来源：评论

学校读者我要写书评

暂无评论

VALKYRIE: a suite of topology-aware clustering approaches for cloud-based virtual network services

引用

JOURNAL OF SUPERCOMPUTING 2023年第3期79卷 3298-3328页

作者： El Mansoum, Imane Lahlou, Laaziz Khasawneh, Fawaz A. Kara, Nadjia Edstrom, Claes Univ Quebec Dept Software Engn & IT Ecole Technol Super Montreal PQ Canada Ericsson Canada Mississauga ON Canada

Complex networks are practical tools for modeling, studying, and analyzing complex interactions between objects. These tools are essential in understanding applications, end-users, interactions between compute nodes, and their behaviors in computer networks. Computer networks are undergoing significant expansion due to the proliferation of network devices and compute nodes. One of the main challenges in computer networks is categorizing these compute nodes into clusters of connected compute nodes within these large-scale structures sharing similar features (e.g., Central Processing Unit, memory, disk storage). This paper proposes a set of novel, dynamic, and proactive topology-aware clustering approaches, namely, an Integer Linear Program, chemical reaction optimization, and a game theory approach that leverages the Irving algorithm, originally proposed to solve the stable roommate problem, to form clusters based on the compute nodes' features and their topological structures. Our proposed techniques are suggested to reduce the search space concerning Network Function Virtualization, Cloud-based Networks deployment, and to build on-demand clusters to meet their requirements. In this regard, the solutions aim to help decision-makers facing issues related to scalability and computational complexities of their mechanisms to deploy their cloud-based services effectively. Experimental results demonstrate the proposed approaches' effectiveness and suitability, given their polynomial-time complexities, making them easy to integrate into cloud providers' orchestration systems compared to K-Means and Density-based spatial clustering of applications with noise.

关键词： Network function virtualization Attributed network infrastructures Clustering multi-objective optimization Topological structure Attribute similarity

来源：评论

学校读者我要写书评

暂无评论

Statistical learning and optimization of the helical milling of the biocompatible titanium Ti-6Al-7Nb alloy

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第3-4期125卷 1789-1813页

作者： da Costa, Tomas Barbosa Dutra Pereira, Robson Bruno Lauro, Carlos Henrique Brandao, Lincoln Cardoso Davim, J. Paulo Univ Fed Sao Joao del Rei Ctr Innovat Sustainable Mfg CIMS Dept Mech & Ind Engn 170 Frei Orlando Sq BR-36880000 Sao Joao Del Rei MG Brazil Univ Fed Sao Joao del Rei Ctr Innovat Modelling & Optimizat Syst CIMOS Dept Mech & Ind Engn 170 Frei Orlando Sq BR-36880000 Sao Joao Del Rei MG Brazil Univ Aveiro Dept Mech Engn Aveiro Portugal

Helical milling has been applied for hole-making in titanium alloys, especially in the Ti-6Al-4V alloy, considering the aims of the aeronautic, automobile, and other sectors. When considering hole-making in Ti-alloys for biomedical applications, few studies have been carried out. Besides, intelligent approaches for modeling and optimization of this process in these special alloys are demanded to achieve the best results in terms of hole surface quality, and productivity. This work presents an approach for modeling and optimization of helical milling for hole-making of Ti-6Al-7Nb biocompatible titanium alloy. The surface roughness of the holes was measured to quantify the hole quality. Principal component analysis was performed for dimensionality reduction of the roughness outputs. For modeling, a learning procedure was proposed considering polynomial response surface regression, tree-based methods, and support vector regression. Cross-validation is used for learning and model selection. The results pointed out that the support vector regression model was the best one. multi-objective evolutionary optimization was performed considering the support vector regression model and the deterministic model of the material removal rate. The Pareto set and the Pareto frontier were plotted and discussed concerning practical aspects of the helical milling process. The proposed learning and optimization approach enabled the achievement of the best results of the helical milling in the biocompatible Ti-6Al-7Nb alloy and can be applied to other intelligent manufacturing applications.

关键词： Helical milling Biocompatible titanium alloy Statistical learning Machine learning Support vector regression multi-objective evolutionary optimization

来源：评论

学校读者我要写书评

暂无评论

A Reconfigurable Cellular Remanufacturing Architecture: a multi-objective design approach

引用

Journal of Remanufacturing 2024年第2期14卷 185-217页

作者： Mejía-Moncayo, Camilo Kenné, Jean-Pierre Hof, Lucas A. Department of Mechanical Engineering École de technologie supérieure 1100 Notre-Dame St W Montreal H3C 1K3 QC Canada

Remanufacturing is a practice that postpones the product ‘end-of-life’ by returning the properties or features of a new product to a used product. Such a process represents an efficient circular economy strategy to extend product life, reducing its environmental footprint. However, remanufacturing systems must overcome distinct challenges related to information uncertainties about quantity and conditions of used products. Current strategies to address these issues include smart approaches towards smart remanufacturing systems. However, remanufacturing architectures must manage the negative effects on operations derived from the used product’s deterioration and return rate variability, as well as remanufactured products demand fluctuations. This study contributes to address this issue by a Reconfigurable Cellular Remanufacturing Architecture that is integrated in a business strategy towards smart sustainable remanufacturing. The design process is based on a multi-objective optimization model that minimizes the grouping cost, the workload balancing cost, the investment cost, the makespan cost and the reconfigurable cost. A customized version of the well-known multi-objective evolutionary non-dominated sorting genetic algorithm II (NSGA2), a mono-objective genetic algorithm (GA-mo) and a GAMS model were implemented to obtain the potential architecture’ configurations for an explanatory case study based on real-world industrial and random data, respectively. Two procedures to identify the best architecture were also considered. A sensitivity analysis is presented to illustrate the robustness of the proposed model. Managerial insights illustrate about solution methods, and best architecture selection. practical implications also are provided to offer useful options for practitioners. © The Author(s), under exclusive licence to Springer Nature B.V. 2024.

关键词： Cellular manufacturing Genetic algorithm multi-objective optimization NSGA2 Reconfigurable manufacturing Remanufacturing Smart manufacturing Uncertainty

来源：评论

学校读者我要写书评

暂无评论

Unconventional Surrogate-Assisted approaches to EM-Driven Antenna Design. Modeling and optimization: Global, multi-objective, Statistical 18

Unconventional Surrogate-Assisted Approaches to EM-Driven An...

引用

18th European Conference on Antennas and Propagation (EuCAP)

作者： Koziel, Slawomir Pietrenko-Dabrowska, Anna Reykjavik Univ Engn Optimizat & Modeling Ctr IS-102 Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland

ISBN: (纸本)9788831299091;9798350394436

Design of contemporary antenna systems relies heavily on full-wave electromagnetic (EM) simulation tools. EM analysis ensures reliability but tends to be computationally expensive, which becomes a serious issue in the context of design automation. In recent years, utilization of surrogate modeling methods has been fostered to alleviate the cost-related difficulties. Yet, the existing procedures typically follow a few major approaches, e.g., different architectural variations of deep neural networks, hyper-parameter/model adjustments in Bayesian optimization, or more or less standard machine learning frameworks. This paper reviews several unconventional surrogate-assisted techniques that employ less common algorithmic tools such as the response feature technology, domain confinement, dimensionality reduction, or supplementary inverse predictors. We demonstrate how these tools can be incorporated into practical procedures for global and multi-criterial optimization, statistical analysis, and design- oriented behavioral modeling. A discussion of the algorithm operating principles is supplemented by antenna design cases.

关键词： Antennas computer-aided engineering design automation EM analysis optimization surrogate modeling

来源：评论

学校读者我要写书评

暂无评论

A multi-objective optimal PMU placement considering fault-location topological observability of lengthy lines: A case study in OMAN grid

引用

ENERGY REPORTS 2023年 9卷 1113-1123页

作者： Al-Hinai, Amer Karami-Horestani, Alireza Alhelou, Hassan Haes Sultan Qaboos Univ Dept Elect & Comp Engn POB 33 Muscat 123 Oman Sultan Qaboos Univ Sustainable Energy Res Ctr Muscat Oman Monash Univ Dept Elect & Comp Syst Engn Clayton Vic 3800 Australia

Using PMU data, the fault location algorithm has gradually been trended in the literature. Besides the optimality of the algorithm, the fault location application should directly receive the data of the faulty line from the PMU devices to have the best performance;using state estimation to create the input data of fault location algorithm not only wastes the golden time, but it also decreases the reliability. Given, it is not possible to install PMU devices in all buses of the system, it is better to install them for the lengthy lines having the most probability of the failure. Although various approaches have been presented in the literature to solve optimal PMU placement (OPP), the fault location observability has less been considered in OPP formulation Accordingly, this paper considers a new index, named fault location observability (FLO), as a second objective function in its OPP formulation. Using this index, in addition to minimizing PMU installation cost, the number of lengthy lines being directly observable are also maximized. Using the epsilon-constraint method, the multi-objective problem has been solved several times as single-objective optimizations. Given the constraints and objective functions are linear, the work presents a mixed integer linear programming (MILP) formulation for the placement problem. Using the GAMS under CPLEX solver, the global optimal solutions of MILP model corresponding to the various epsilon-constraints yields to a Pareto optimal front. The simulation results, next, implements the proposed method on the IEEE 300 bus test system as well as the practical OMAN grid to prove the effectiveness of the proposed method.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Phasor measurement unit Optimal PMU placement OMAN grid Fault location observability (FLO) index MILP-based multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

MFRL: A model-free reinforcement learning model for energy storage in microgrid systems

引用

EXPERT SYSTEMS WITH APPLICATIONS 2025年 288卷

作者： Tang, Chao Qin, Yunchuan Wu, Fan Tang, Zhuo State Grid Hunan Elect Power Co Ltd Informat & Commun Branch Changsha 410029 Hunan Peoples R China Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Hunan Peoples R China

With the rapid development of renewable energy and the rise of microgrid systems, the role of energy storage technology in these systems is becoming increasingly important. Traditional energy storage control approaches often require the establishment of complex physical models. However, due to the complexity and uncertainty of microgrid systems, these models often encounter numerous difficulties and inaccuracies, which limit the performance and stability of the systems. In this paper, we propose a novel model-free reinforcement learning (MFRL) framework for optimizing energy storage strategies in microgrid systems, distinguishing itself by integrating multiple key stakeholders, including energy providers and end-users, into the system model. Different from existing studies that usually focus on simplified or single-agent models, our approach considers the interactions and different priorities of all relevant parties including energy suppliers and end-users, thus providing a more comprehensive system model. Based on this, we design the MFRL algorithm by combining the agent-based reinforcement with optimization strategies. MRFL autonomously learns the power procurement and consumption behavior of microgrid systems using Monte Carlo methods, and obtains the optimal power procurement and storage strategies. In addition, we further design a dynamic decision-making mechanism to enhance the adaptability of the system, enabling it to respond to changing operating conditions in real time. This mechanism can quickly adapt to changes in the microgrid operating environment across different scales. We conduct extensive simulations and practical experiments to verify the effectiveness of MRFL in adapting to dynamic operating conditions. The experimental results indicate that MRFL outperforms the state-of-the-art methods in terms of average return, providing a sustainable and efficient solution for optimizing energy storage in microgrids.

关键词： Energy storage Microgrid systems Model-free reinforcement learning multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

Addressing uncertainty in closed-loop supply chain networks: a multi-objective approach to integrated production and transportation problems

引用

JOURNAL OF MODELLING IN MANAGEMENT 2024年第6期19卷 1849-1882页

作者： Varshney, Niharika Gupta, Srikant Ahmed, Aquil Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India Jaipuria Inst Management Dept Operat & Decis Sci Jaipur Rajasthan India

PurposeThis study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective ***/methodology/approachIn dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC *** research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain *** limitations/implicationsThis study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain ***/valueThis research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and d

关键词： optimization Sensitivity Supply chain management Operations research

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：