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检索条件"主题词=Mixed integer linear programming"

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A Deep Q-Learning Framework for Enhanced QoE and Energy Optimization in Fog Computing

A Deep Q-Learning Framework for Enhanced QoE and Energy Opti...

引用

International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Sabiha Tasnim Sumona Syed Sabbir Hasan Abu Yousuf Tamzid Palash Roy Md. Abdur Razzaque Redowan Mahmud Department of Computer Science and Engineering Green University of Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Green Networking Research Group University of Dhaka Bangladesh School of Electrical Engineering Computing and Mathematical Sciences Curtin University Australia

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Fog computing, an evolution of cloud computing, has become increasingly popular for its ability to lessen the burden of such a centralized computing paradigm by distributing tasks generated by IoT across fog layers. Effectively managing real-time, delay-sensitive, and diverse IoT applications to enhance the Quality-of-Experience (QoE) presents significant challenges due to the dispersed nature and limited resources of fog nodes. Previous studies in fog computing task offloading have typically focused on either energy consumption or service delay. This paper introduces an optimization framework for task offloading within fog computing environments that aims to balance improved user QoE with reduced energy consumption, employing mixed-integer linear programming (MILP). Given the NP-hard nature of this framework, we have devised a Deep Q-Learning (DQL) based model for task offloading, termed ELTO-DQL, which aims for near-optimal solutions in polynomial time. Experimental results indicate that the ELTO-DQL model enhances energy efficiency and QoE by up to 19% and 15% respectively, outperforming contemporary benchmarks.

关键词： Energy consumption Q-learning Computational modeling mixed integer linear programming Quality of experience Internet of Things Resource management

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Scalable Approximate Optimization of Objective Functions Represented by Random Forests

Scalable Approximate Optimization of Objective Functions Rep...

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Mediterranean Conference on Control and Automation (MED)

作者： Marco Leonesio Lorenzo Fagiano Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing - National Research Council of Italy (STIIMA - CNR) Milano Italy Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Piazza Milano Italy

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

The problem of global optimization of an objective function represented by a Random Forest (RF) is considered. A method to obtain an approximate solution at low computational complexity is proposed, resorting to the inherent structure of an RF, which is a non-parametric model that partitions the feature space in convex polytopes according to the training data. The approach selects the optimal solution inside the polytopes corresponding to the best data points. It is shown that the proposed approximate method is significantly more efficient, thus applicable at large scale, than extensive global search algorithms, such as gridding and mixed integer linear programming (MILP), which in turn provide exact solutions. The efficiency and sub-optimality of the approach are evaluated on RFs trained on a dataset generated by sampling a bivariate, discontinuous and non-convex benchmark function from the literature.

关键词： Radio frequency Computational modeling Training data linear programming Data models Partitioning algorithms mixed integer linear programming

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An Optimal Algorithm for Low Power Multiplierless FIR Filter Design using Chebychev Criterion

An Optimal Algorithm for Low Power Multiplierless FIR Filter...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Georgios Karakonstantis Kaushik Roy School of Electrical and Computer Engineering Purdue University USA

In this paper, we propose a novel finite impulse response (FIR) filter design methodology that reduces the number of operations with a motivation to reduce power consumption and enhance performance. The novelty of our approach lies in the generation of filter coefficients such that they conform to a given low-power architecture, while meeting the given filter specifications. The proposed algorithm is formulated as a mixed integer linear programming problem that minimizes Chebychev error and synthesizes coefficients which consist of pre-specified alphabets. The new modified coefficients can be used for low-power VLSI implementation of vector scaling operations such as FIR filtering using computation sharing multiplier (CSHM). Simulations in 0.25 μm technology show that CSHM FIR filter architecture can result in 55% power and 34% speed improvement compared to carry save multiplier (CSAM) based filters.

关键词： Finite impulse response filter Algorithm design and analysis Design methodology Energy consumption mixed integer linear programming Very large scale integration Vectors Filtering Computational modeling Computer architecture

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Cyber-Vulnerability Analysis for Real-Time Power Market Operation

Cyber-Vulnerability Analysis for Real-Time Power Market Oper...

引用

IEEE General Meeting Power& Energy Society

作者： Qiwei Zhang Fangxing Li Electrical Engineering University of Tennessee Knoxville ECE University of Tennessee Knoxville

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408240

With the rapid advancement and integration of communication and sensor technologies, power system operation is becoming more vulnerable to cyberattacks, particularly attacks in which malicious data could induce catastrophic consequences on market operations. Financial risks, as well as the potential physical damages, raise growing concerns about the reliable operation of the electricity market. Existing market-targeting cybersecurity research has focused on developing attack strategies or detection schemes. However, the lack of cyber-vulnerability analysis (CVA) hinders operators from systematically evaluating the real-time (RT) market-clearing model and identifying potential threats from a cybersecurity perspective. This article proposes a comprehensive CVA model for delivering a detailed analysis of four aspects of vulnerability: highly probable cyberattack targets, devastating attack targets, risky load levels, and mitigation ability under different degrees of defense. Users can simulate interactions between attackers and defending operators under different attack events, and the corresponding market settlements are also obtained. The proposed bilevel model is recast into mixed-integer linear programming through Karush-Kuhn-Tucker (KKT) conditions. A simulation study on an IEEE-30 bus system demonstrates the accuracy and effectiveness of the proposed CVA model.

关键词： Electric potential Analytical models Electricity supply industry Real-time systems Power markets Power system reliability mixed integer linear programming

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A Computationally Efficient Approach to Account for Stochastic Delays in Multi-Robot Task Allocation in a Proactive Manner

A Computationally Efficient Approach to Account for Stochast...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Shengqiang Chen Quan Nguyen Satyandra K. Gupta Department of Aerospace and Mechanical Engineering University of Southern California Los Angeles CA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Delays play an important role in the overall performance of multi-robot missions. Delays can be handled in a reactive manner by replanning or can be handled proactively by selecting task allocations that are robust to delays. mixed integer linear programming (MILP) has emerged as a useful tool for solving multi-robot task allocation problems. The possibility of delays can be incorporated by sampling many different delay scenarios and generating an optional solution for each scenario. The solution that leads to the most robust performance is selected as the overall solution. Unfortunately, generating a large number of delay scenarios and computing the robustness of each solution by evaluating it using every sampled delay scenario is computationally very slow. This paper presents a method for speeding up computations by pruning solutions based on a similarity index. We evaluate the proposed approach using assembly and disinfection applications. We show that our approach leads to very good solutions with a modest computational effort.

关键词： Computer aided software engineering Automation Machine learning Robustness Probability distribution Delays Computational efficiency mixed integer linear programming Resource management Indexes

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A Solution Based on Hub Selection and Robot Routing Optimization for Last-mile Delivery

A Solution Based on Hub Selection and Robot Routing Optimiza...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Maria A. del Cacho Estil-les Wasim A. Ali Maria Pia Fanti Mario Binetti Agostino M. Mangini Department of Electrical and Information Engineering Polytechnic of Bari Italy DICATECh Polytechnic of Bari Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This paper addresses the challenges in last-mile delivery by proposing an innovative solution employing Hub-and-Robots routing, strategically utilizing park-and-ride facilities as central hubs to optimize urban delivery operations. The increasing demand for rapid and efficient deliveries has necessitated a reevaluation of traditional delivery methodologies. The study focuses on optimizing last-mile delivery operations, minimizing the total distance of the routes traveled by robots, while satisfying customer requirements. Hub selection, leveraging existing infrastructure, and the potential use of park-and-ride facilities emerge as key considerations. The optimization model is applied to a case study involving two districts of the center of Bari (a city of Southern Italy) and a simulation validates the obtained results.

关键词： Systematics Computer aided software engineering Optimization models Scalability Heuristic algorithms Urban areas Routing mixed integer linear programming Resource management Optimization

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Minimum-energy multicast routing in static wireless ad hoc networks

Minimum-energy multicast routing in static wireless ad hoc n...

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IEEE Conference on Vehicular Technology (VTC)

作者： Song Guo O.W. Yang School of Information Technology and Engineering University of Ottawa Ottawa ONT Canada

Wireless mobile ad hoc stations have limited battery capacity. One major performance metric used to evaluate broadcast and multicast trees is the lowest total energy consumption. We extend our previous work by presenting a more general study from the broadcast to multicast case, since the multicast tree obtained by pruning some broadcast tree does not give good performance once the multicast group sizes are small. We present a constraint formulation in terms of MILP (mixed integer linear programming), which can be used for an optimal solution of the minimum-energy multicast (MEM) problem in wireless ad hoc networks with omnidirectional antennas. Experimental results show that an optimal solution of the MEM problem using our MILP model can always be obtained in a timely manner for moderately sized networks, typically with 50 nodes.

关键词： Routing Intelligent networks Ad hoc networks Broadcasting mixed integer linear programming Mobile ad hoc networks Information technology Power engineering and energy Batteries Energy consumption

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Specialized Genetic Algorithm to Solve the Electrical Distribution System Expansion Planning

Specialized Genetic Algorithm to Solve the Electrical Distri...

引用

IEEE Power and Energy Society General Meeting

作者： Vera Camargo Marina Lavorato Rubén Romero Department of Mathematics of Sinop Mato Grosso State University Sinop – MT Brazil Faculty of Engineering of Ilha Solteira Paulista State University Ilha Solteira - SP Brazil

ISBN: (纸本)9781479913022

A specialized genetic algorithm with a adaptation of Chu-Beasley algorithm is presented in this paper to solve the electrical distribution distribution system expansion planning (DSP) problem modeled by a mixed integer nonlinear programming problem. The specialized genetic algorithm proposed in this paper starting from a initial population where all elements have a radial topology found using a heuristic algorithm and after the selection and mutation operations must also go through a local improvement in order to make the proposed solution in a feasible solution, if necessary, with respect to operational constraints. The DSP problem presented in this paper consider the circuit construction/recondutoring for different types of conductors and the substation construct/reinforcement. To evaluate the quality of the proposed methodology were used three different test systems found in the literature, 23, 54 and 136 buses systems.

关键词： Distribution network planning genetic algorithm mixed integer nonlinear programming power systems optimization. power distribution planning Genetic Algorithm (GA) Electricity Distribution Systems system optimization expansion plan mixed integer linear programming power system expansion planning Feasible Solution

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Research of Greenhouse Heating Based on Photovoltaic, Heat Pump and Thermal Storage System: A Case Study in Beijing

Research of Greenhouse Heating Based on Photovoltaic, Heat P...

引用

Energy Engineering and Power Systems (EEPS), International Conference on

作者： Zhehan Zhong Jixue Wang Guodong Chen Bing Liu Xiaolei Li Shuo Yang Zheng Li Electric Power Planning & Engineering Institute Beijing China Department of Energy and Power Engineering Tsinghua University Beijing China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

This study focuses on the global demand for renewable energy heating, and proposes a scheme that combines photovoltaic panels, heat pumps, and thermal storage to offer heat to agricultural greenhouses. Initially, a computational model of the system is developed, with the economic aspect as the objective function, energy and power balances as constraints, actual meteorological conditions of Beijing as boundary conditions. Subsequently, the model is optimized through the MILP (mixed integer linear programming) in Gurobi to ascertain the minimal annual cost of the system and the scales of its components. Finally, a comparative analysis with the prevailing heating price of Beijing reveals the proposed scheme's technological and financial viability.

关键词： Photovoltaic systems Renewable energy sources Costs Heat pumps Cogeneration Computational modeling Greenhouses linear programming mixed integer linear programming Resistance heating

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Reliability Assessment of Distribution Systems Considering the Effects of Cyber Failures

Reliability Assessment of Distribution Systems Considering t...

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Intelligent Power and Systems (ICIPS), International Conference on

作者： Xuan Fang Wenrui Zhou Jiahao Liang Juntao Li Siguang Zheng Bohuai Yan Guangzhou Bureau of China Southern Power Grid EHV Transmission Company Guangzhou China College of Electrical Engineering & New Energy China Three Gorges University Yichang China The School of Electrical and Information Engineering Tianjin University China College of Science Hongkong Baptist University Hongkong China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

The traditional reliability assessment methods for cyber-physical distribution systems suffer from low computational efficiency and accuracy, as well as insufficient consideration of cyber systems. This article deeply analyzes the impact of cyber systems failures on the reliability of distribution networks, and uses optimization methods to solve the reliability of distribution systems. The reliability assessment method proposed in this article has the advantage of precise evaluation.

关键词： Accuracy Optimization models Distribution networks Planning mixed integer linear programming Computational efficiency Reliability Information systems

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