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Energy-saving optimization of application server clusters based on mixed integer linear programming

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2023年 171卷 111-129页

作者： Xiong, Zhi Zhao, Min Yuan, Ziyue Xu, Jianlong Cai, Lingru Shantou Univ Dept Comp Sci & Technol Shantou 515063 Peoples R China Shantou Univ Minist Educ Key Lab Intelligent Mfg Technol Shantou 515063 Peoples R China

The issue of how to dynamically optimize the deployment of an application server cluster according to the changing load to reduce energy consumption is an important problem that must be urgently solved. In this paper, we propose an energy-saving optimization strategy for application server clusters, whose optimization content includes the on/off state, CPU frequency, and load size of each server. Compared with existing research, our strategy is not only more accurate in power and load models but also considers the switching cost of servers to avoid server switching jitter. The strategy includes two schemes, which both formulate the cluster energy-saving optimization as a mixed integer linear programming (MILP) problem and then adopt a toolkit to solve the problem. One scheme defines variables for each server, and the resulting programming problem is called the MILP4PH problem. The other scheme defines variables for each server type, resulting in a programming problem called the MILP4GH problem. The experimental results reveal that for clusters with poor homogeneity, the MILP4PH problem has fewer variables and can be solved in real time, while for clusters with good homogeneity, the MILP4GH problem has fewer variables and can be solved in real time.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Application server cluster Energy-saving optimization mixed integer linear programming Switching jitter Homogeneity

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Integrating random regret minimization-based discrete choice models with mixed integer linear programming for revenue optimization

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Iran Journal of Computer Science 2024年第1期8卷 21-35页

作者： Talebi, Amirreza Haeri Boroujeni, Sayed Pedram Razi, Abolfazl Department of Integrated Systems Engineering The Ohio State University Columbus OH United States School of Computing Clemson University Clemson 29632 SC United States ENSIMAG Grenoble Alpes University Grenoble France

This paper explores the critical domain of revenue management (RM) within operations research (OR), focusing on intricate pricing dynamics. Utilizing mixed integer linear programming (MILP) models, the study enhances revenue optimization by considering product prices as decision variables and emphasizing the interplay between demand and supply. Recent advancements in discrete choice models (DCMs), particularly those rooted in random regret minimization (RRM) theory, are investigated as potent alternatives to established random utility maximization (RUM)-based DCMs. Despite the widespread use of DCMs in RM, a significant gap exists between cutting-edge RRM-based models and their practical integration into RM strategies. The study addresses this gap by incorporating an advanced RRM-based DCM into MILP models, addressing pricing challenges in both capacitated and uncapacitated supply scenarios. The developed models demonstrate the feasibility and offer diverse interpretations of consumer choice behavior, drawing inspiration from established RUM-based frameworks. This research contributes to bridging the existing gap in the application of advanced DCMs within practical RM implementations. © This is a U.S. Government work and not under copyright protection in the US;foreign copyright protection may apply 2024.

关键词： Choice-based optimization Decision-making behavior Demand prediction mixed integer linear programming Operations research Pricing

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Neural Network-based Lyapunov Stability Verification for Continuous-time Nonlinear Systems via mixed integer linear programming 9

Neural Network-based Lyapunov Stability Verification for Con...

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9th International Conference on Control and Robotics Engineering (ICCRE)

作者： Wang, Jingya Yu, Yongbin Wang, Xiangxiang Feng, Xiao Han, Xinyi Cai, Jingye Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Peoples R China

ISBN: (纸本)9798350372694;9798350372700

This paper discusses Lyapunov stability verification methods for continuous-time nonlinear systems. Traditional mathematical methods require a lot of manual calculations, which consume a lot of time and energy. To address the problem of the low efficiency in traditional methods, this paper introduces neural networks into the design of the Lyapunov function to achieve independent verification. First, a neural network is used to represent the Lyapunov function. Then, the Lyapunov stability condition is converted into a mixed integer linear programming (MILP) problem, and the solution to the optimization problem is solved through the MILP solver to verify whether the output of the neural network satisfies the Lyapunov stability condition. In addition, this paper gives the training loss function of the Lyapunov neural network, which mainly consists of optimization problems. Finally, a simulation example is given to illustrate the effectiveness of this method.

关键词： neural networks Lyapunov function continuous-time nonlinear systems mixed integer linear programming

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Efficient mixed integer linear programming Approaches to Dynamic Path Restoration 12

Efficient Mixed Integer Linear Programming Approaches to Dyn...

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12th IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Rubtsov, Alexander Bauwens, Bruno Shmelkin, Dmitri Rudenko, Elizaveta Lavrov, Alexey HSE Univ Fac Comp Sci Moscow Russia Independent Univ Moscow Moscow Russia HSE Univ Fac Math Moscow Russia

ISBN: (纸本)9798350351866;9798350351859

We consider the problem of single link failure in an elastic optical network, (also known as flex-grid WDM network). The task is to reroute optical connections that go through the broken link using free capacity of other links of the network. Nowadays, dynamic restoration gains popularity, in which the possiblity of rerouting is only inspected after a link failure is detected. Since the problem of recovery is NP-hard, heuristic algorithms are used to either find such routes, or suggest that the routes do not exist. In order to understand the quality of these heuristics, often mixed integer linear programming is used to obtain exact positive and negative answers. We present a detailed such model that checks whether restoration is possible without the use of additional regenerators. This means, that the new light paths need to satisfy a length constraint. As preprossing we apply a trimming procedure that takes advantage of this length constraint, and significantly speeds up the evaluation of these models. Our model is more general, and besides solving the problem of link restoration, also solves the full problem of wavelength and spectrum assignment.

关键词： mixed integer linear programming Routing and Spectrum Allocation Problem Combinatorial Optimization

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Enhancing expansion of rooftop PV systems through mixed integer linear programming and Public Tender Procedures

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RENEWABLE ENERGY 2022年第0期187卷 347-361页

作者： Georgiou, Giorgos S. Rouvas, Constantinos Nathanael, Demetris Elect Author Cyprus Dept Nonregulated Act Strovolos Cyprus Cyprus Univ Technol Dept Elect Engn Comp Engn & Informat Limassol Cyprus Elect Author Cyprus Generat Unit Strovolos Cyprus Elect Author Cyprus Procurement Dept Strovolos Cyprus

Concerning the growth rate in Renewable Energy share, especially in the EU, it is fact that Rooftop PV systems have a significant role to play. Nevertheless, it is also accepted that with current policies, schemes and scientific methods, today's Renewable Energy growth rate is still far from the desired one. Based on that, this study proposes a novel integration of a mixed-integer linear programming based model in a Public Tender Procedure, which enables the bulk installation and thus, the rapid expansion of Rooftop PV systems, in a least-cost manner. The main objective and contribution of this paper is to provide an economic solution to interested Public Bodies for utilizing the rapid growth of rooftop PV systems through novel mechanisms and hence, to better achieve the desired Renewable Energy targets. To further highlight the capabilities of the proposed method, the results from a real-life project, showed that the bulk installation of PV systems, in 404 public schools with a total PV capacity of 4.8 MWp, can be realized at an optimum cost. The main achievements are: (i) high-level competition, due to the ability of the proposed model to select multiple PV Installers, (ii) a 35% lower project cost compared to the initial estimated budget and (iii) a significantly lower unit cost of about 0.7 million euro/MWp, compared to about 0.91 and 1.54 million euro/MWp obtained from other similar projects. Finally, the outcomes of the proposed MILP model are validated by those obtained from an exhaustive optimal solution search procedure. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Building integrated PV Novel renewable energy growth mechanisms mixed integer linear programming Public procurement

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Variable Speed Limit and Ramp Metering Control of Highway Networks Using Lax-Hopf Method: A mixed integer linear programming Approach

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第7期23卷 7441-7456页

作者： Vishnoi, Suyash C. Claudel, Christian G. Univ Texas Austin Dept Civil Architectural & Environm Engn Austin TX 78712 USA

This paper presents a novel optimization formulation to solve the problem of variable speed limit control on road networks modeled by the Lighthill-Whitham-Richards (LWR) partial differential equation. It also presents some mathematical rules that allow for a reduction in the size and computational time of the optimization problem. Using the analytical solutions to the LWR model, an optimization problem is formulated for the variable speed limit and ramp metering control of traffic on highway networks using the Lax-Hopf algorithm. The resulting problem, which is non-linear in the decision variables, is transformed into a mixed integer linear Program. An example is presented to show the effectiveness of the approach, including its application to a real-world highway network with multiple ramp connections. The possibility of linear relaxation of integer variables in the problem is also considered. Lastly, the method is compared to a classical Link Transmission Model formulation of the variable speed limit control problem.

关键词： Lax-Hopf method variable speed limits network control mixed integer linear programming

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Enhancement of battery life in microgrid energy management using mixed integer linear programming and hybrid knapsack

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2022年第6期46卷 8158-8174页

作者： Gounder, Yasoda Kailasa Subramanian, Sowkarthika Govt Coll Technol Dept Elect & Elect Engn Coimbatore Tamil Nadu India

Microgrid with distributed energy resources and energy storage system provides sustainability and resiliency. In this research, residential community microgrid is examined with responsive loads that create flexible generation-demand model. An optimization algorithm using mixed integer linear programming (MILP) has been formulated to minimize the operating cost and emission of dispatchable power generation, with the help of demand response. Usually, in renewable energy-based grid-connected microgrid, the batteries are managed under partial state of charge (SoC) conditions due to the limit of power imported from grid. The proposed MILP model ensures full SoC operation and safe charging or discharging dynamics of the battery in order to enhance its lifespan. Moreover, the day-ahead scheduling of household appliances is carried out using a novel hybrid knapsack method, which combines binary and fractional knapsack algorithms. An electric vehicle battery is considered as a flexible power load, which offers an unique way of approach in scheduling of appliances. The results confirm that the power demanded by the appliances is fulfilled at the user-specified hour for maximum comfort along with minimum operating cost of microgrid. Generic algebraic modeling system (GAMS) tool is used to run the proposed algorithms.

关键词： day-ahead scheduling knapsack lifetime of battery microgrid mixed integer linear programming

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Research on Task Allocation of Multi-constraint Unmanned System Swarm Based on mixed integer linear programming

Research on Task Allocation of Multi-constraint Unmanned Sys...

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International Conference on Autonomous Unmanned Systems (ICAUS)

作者： Tu, Long Liu, Shulei Yan, Ye Yao, Wen Chang, Qiang Natl Innovat Inst Def Technol Beijing Peoples R China Xidian Univ Xian Peoples R China

ISBN: (纸本)9789819904815;9789819904792;9789819904785

Unmanned systems swarm task allocation is one of the key issues of unmanned systems collaborative control. Aiming at the multiple objectives and multiple constraints task allocation issue of unmanned systems swarm, under the multi-constrained conditions of comprehensively considering the benefits of unmanned systems swarm against multiple targets, weapon costs, disabling costs, time costs and energy costs, taking the largest net income, the smallest number of unmanned systems dispatched, and the least number of weapons carried by unmanned systems as the optimization goals respectively, the mathematical models of multi-constrained task allocation based on mixed integer linear programming is established. The Cplex solver is used to solve the specific examples. And the calculation results are analyzed. The results show that the task allocation model based on "platform-weapon-target" can effectively solve the assignment issue of multi-constraint unmanned system swarm.

关键词： Mission planning mixed integer linear programming Task allocation

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Multi-Period Optimization of Hybrid Energy Systems Using mixed integer linear programming

Multi-Period Optimization of Hybrid Energy Systems Using Mix...

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IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)

作者： Alhashedi, Salah Khan, Khalid A. Alowaifeer, Maad Khalid, Muhammad King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia KFUPM Ctr Renewable Energy & Power Syst Dhahran 31261 Saudi Arabia KFUPM SDAIA KFUPM Joint Res Ctr Artificial Intelligence Dhahran 31261 Saudi Arabia

ISBN: (纸本)9798350332117

The integration of hybrid energy systems (HES) into the electric power grid is gaining traction due to the need of establishing a clean and sustainable energy system for satisfying the increasing load demand. Such integration enables integration of renewable energy sources in the form of HES that is scalable from small as well as large-scale integration. Nevertheless, the commonly preferred renewable energy sources (RESs), such as, solar and wind energy have significantly limited economic feasibility owing to their unpredictability and intermittency. Energy storage systems (ESSs) are among the key solutions to mitigate the impact of variable renewable energy sources on the grid by acting as an energy buffer. In this paper, a multiperiod optimization technique is formulated for the appropriate scheduling of ESSs in a HES that acts as a model of a residential district consisting of several houses with installed PV systems and connections to the main electricity grid. To further verify the method's effectiveness, the results are obtained for both summer and winter season scenarios.

关键词： Energy storage systems hybrid energy system mixed integer linear programming multi-period optimization solar photovoltaics

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Spread-Out Bragg Peak in Treatment Planning System by mixed integer linear programming: a Proof of Concept 36

Spread-Out Bragg Peak in Treatment Planning System by Mixed ...

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36th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

作者： Spezialetti, Matteo de Lorenzo, Ramon Gimenez Gravina, Giovanni Luca Placidi, Giuseppe Rossi, Fabrizio Russo, Giorgio Smriglio, Stefano Vittorini, Francesca Mignosi, Filippo Univ Aquila DISIM Dept Laquila Italy San Salvatore Hosp Med Phys Unit ASLI Coppito Abruzzo Italy Univ Aquila DISCAB Dept Laquila Italy Univ Aquila MESVA Dept Laquila Italy Inst Mol Bioimaging & Physiol IBEM CNR Palermo Italy

ISBN: (纸本)9798350312249

In this paper we analyze different mixed integer linear programming (MILP) models in order to produce 1D and 3D Spread-Out Bragg peaks (SOBP) for protons in water. Our techniques do not use much computational resources;in particular, all our experiments have been performed by a standard personal computer. As main result we give the proof of concept that the techniques that we use to create parameterized uniform SOBP can be fruitfully used in Treatment Planning Systems (TPS) for Intensity Modulated Proton Therapy (IMPT). As technical result we show, for the first time to our best knowledge, that there is a trade-off between the minimum number of energies (or layers) to be used to have a SOBP peak within a uniformity tolerance parameter Dt and the same parameter Dt. Minimizing the number of energies also has the advantage of reducing the delivery time using the facilities in operation nowadays.

关键词： Treatment Planning Systems Proton Therapy Computational Resources Spread-out Bragg Peak mixed integer linear programming

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