检索结果-内蒙古大学图书馆

Exploring Enhanced Dominant Resource Fairness Using linear programming Calculated Weights 17

学校读者我要写书评

暂无评论

Exploring Enhanced Dominant Resource Fairness Using Linear P...

17th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2024

作者： Yan, Bo Beltre, Angel Saha, Pankaj Govindaraju, Madhusudhan BinghamtonNY United States Sandia National Laboratories United States

ISBN: (纸本)9798350367201

Maintaining resource fairness while achieving optimization for various performance metrics such as resource utilization, turnaround time and job latency is a well-known resource scheduling challenge in cloud computing. Despite the significant progress made with the introduction of dominant resource fairness by Ghodsi et al., which ensures major allocation properties such as sharing incentive, strategy-proofness, envy-freeness and Pareto efficiency to be achieved, in practice, strict adherence to fairness may still lead to non-optimized utilization of resources when a series of jobs are scheduled on a shared computing infrastructure. On the other hand, prioritizing optimization without consideration for fairness is not acceptable. Therefore, there is a need for an approach that can address both fairness and optimization. In this paper, we present LPWD, an enhanced Dominant Resource Fairness based scheduling approach that utilizes linear programming based calculated weights to balance fairness with user-specific configurable optimization objective. LPWD maintains relative and proportional fairness and employs linear programming to conduct dynamic resource allocation planning for arriving jobs on-the-fly and generate weights for each job based on a multi-objective optimization. These calculated weights are then applied to the weighted dominant resource fairness policy that guides the reordering of the jobs in the queue before deployment to the cloud. We have implemented and evaluated LPWD in a Kubernetes cluster hosted on the Chameleon cloud infrastructure, which is a configurable platform widely used by scientific communities. Our workloads are based on normalized Google trace data and Alibaba trace data and capture characteristics of resource demands in a real-world production setting. The experimentation with LPWD shows that it leads to resource utilization improvement up to 7.62% and overall turnaround time improvement up to 8.21% while maintaining job latency. © 2

关键词： linear programming

Convex Lyapunov Functions for Switched Discrete-Time Systems by linear programming

学校读者我要写书评

暂无评论

Convex Lyapunov Functions for Switched Discrete-Time Systems...

International Carpathian Control Conference (ICCC)

作者： Juan Javier Palacios Roman Sigurdur Hafstein Department of Mechanical Engineering Eindhoven University of Technology Eindhoven the Netherlands Faculty of Physical Sciences University of Iceland Reykjavik Iceland

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

We present a novel method to compute convex Lyapunov functions for discrete-time, switched systems. The individual subsystems are assumed to be linear. The method uses linear programming to construct continuous piecewise affine and convex Lyapunov functions for the switched system. We demonstrate the applicability of our method with two examples from the literature.

关键词： Switched systems linear systems Discrete-time systems Asymptotic stability Switches programming linear programming

A PRECONDITIONER FOR SOLVING linear programming PROBLEMS WITH DENSE COLUMNS

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Villalba, Catalina J. Oliveira, Aurelio R.L. Campinas Brazil

The Interior-Point Methods are a class for solving linear programming problems that rely upon the solution of linear systems. At each iteration, it becomes important to determine how to solve these linear systems when the constraint matrix of the linear programming problem includes dense columns. In this paper, we propose a preconditioner to handle linear programming problems with dense columns, and we prove theoretically that the final linear system to solve is uniformly bounded when the Interior-Point Method is converging to an optimal solution. This result is illustrated through computational experiments, which show that our proposed method is robust and competitive in terms of running time and/or number of iterations compared with existing methods. © 2024, CC BY-NC-ND.

关键词： linear programming

FROM linear programming TO COLLIDING PARTICLES

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Black, Alexander E. Lütjeharms, Niklas Sanyal, Raman Dept. Mathematics Univ. of California DavisCA95616 United States Institut für Mathematik Goethe-Universität Frankfurt Frankfurt am Main Germany

Although simplices are trivial from a linear optimization standpoint, the simplex algorithm can exhibit quite complex behavior. In this paper we study the behavior of max-slope pivot rules on (products of) simplices and describe the associated pivot rule polytopes. For simplices, the pivot rule polytopes are combinatorially isomorphic to associahedra. To prove this correspondence, we interpret max-slope pivot rules in terms of the combinatorics of colliding particles on a line. For prisms over simplices, we recover Stasheff’s multiplihedra. For products of two simplices we get new realizations of constrainahedra, that capture the combinatorics of certain particle systems in the *** Codes 90C05, 90C57, 52B12, 52B11 Copyright © 2024, The Authors. All rights reserved.

关键词： linear programming

Secrecy Coding for the Binary Symmetric Wiretap Channel via linear programming

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Nikkhah, Ali Shoushtari, Morteza Akhbari, Bahareh Harrison, Willie K. The Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran16317-14191 Iran The Department of Electrical and Computer Engineering Brigham Young University ProvoUT84602 United States The Department of Computer and Information Science Linköping University Sweden

In this paper, we use a linear programming (LP) optimization approach to evaluate the equivocation for a wiretap channel where the main channel is noiseless, and the wiretap channel is a binary symmetric channel (BSC). Using this technique, we present an analytical limit for the achievable secrecy rate in the finite blocklength regime that is tighter than traditional fundamental limits. We also propose a secrecy coding technique that outperforms random binning codes. When there is one overhead bit, this coding technique is optimum and achieves the analytical limit. For cases with additional bits of overhead, our coding scheme can achieve equivocation rates close to the new limit. Furthermore, we evaluate the patterns of the generator matrix and the parity-check matrix for linear codes and we present binning techniques for both linear and non-linear codes using two different approaches: recursive and non-recursive. To our knowledge, this is the first optimization solution for secrecy coding obtained through linear programming. Copyright © 2024, The Authors. All rights reserved.

关键词： linear programming

First-Order Methods for linear programming

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Lu, Haihao

linear programming is the seminal optimization problem that has spawned andgrown into today\'s rich and diverse optimization modeling and algorithmiclandscape. This article provides an overview of the recent development offirst-order methods for solving large-scale linear programming. Copyright © 2024, The Authors. All rights reserved.

关键词： linear programming

A linear programming Approach to Carpooling: Enhancing Commute Efficiency at Federal University of Technology Minna

学校读者我要写书评

暂无评论

A Linear Programming Approach to Carpooling: Enhancing Commu...

Communications, Information, Electronic and Energy Systems (CIEES), International Conference on

作者： H S Abdulrahman Ali Almusawi Rapheal Temitayo Bamisaye Syed Shah Sultan Mohiuddin Qadri Kamran Dawood Dept. of Civil Engineering Federal University of Technology Minna Nigeria Dept. of Civil Engineering Çankaya University Ankara Türkiye Dept. of Industrial Engineering Çankaya University Ankara Türkiye Senior R&D Specialist Astor Enerji Ankara Türkiye

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

This study explores the development of a carpooling system specifically designed for the Federal University of Technology Minna staff, utilizing the Civil Engineering Department as a case study. Amidst the escalating concerns of environmental sustainability, traffic congestion, and the economic burdens of individual commuting, carpooling presents itself as a sustainable alternative. Employing a mixed-methods approach, this research integrates a comprehensive survey to assess staff attitudes towards carpooling with the development of a linear programming model aimed at optimizing vehicle routes and allocations. The findings from the survey indicate a significant willingness among the staff to engage in carpooling, motivated by the anticipated benefits such as cost savings and reduced commuting times. The linear programming model further validates the practicality of substantially lowering total travel distances and emissions when compared to solo commuting practices. This targeted investigation showcases the carpooling system's capability not only to enhance commute efficiency among university staff but also positions it as a replicable and sustainable model for other academic institutions. The study contributes valuable insights into the design and operationalization of effective carpooling strategies within the university landscape, proposing a scalable framework applicable to similar urban contexts.

关键词： Surveys Privacy Costs Green products Transportation linear programming Resource management Carbon emissions Traffic congestion Optimization

An Efficient linear programming Model for Dual-arm Cluster Tools with Chamber Cleaning Operation

学校读者我要写书评

暂无评论

An Efficient Linear Programming Model for Dual-arm Cluster T...

IEEE International Conference on Networking, Sensing and Control

作者： GuanZhong Wu ChunRong Pan WenQing Xiong Lifa He School of Mechanical and Electrical Engineering Jiangxi University of Science and Technology Ganzhou China Longnan Junya Flexible Intelligent Technology Co Ganzhou China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

In semiconductor manufacturing, a cluster tool consists of loadlocks, several processing chambers and a robot for transporting wafers. During wafer fabrication, a chamber needs cleaning for removing residual gases and solid particles to reduce risk of contamination wafer surface. Chamber cleaning makes the scheduling problem of cluster tools more complicated, which leads to deadlock. The method based on virtual wafer can avoid such problem, but this method also reduces chamber utilization. Aiming to improve the throughput of cluster tools with chamber cleaning, this paper modifies robot sequences and adjusts the processing time of virtual wafer. Then, based on the time characteristics of the system, a linear programming model is established to achieve the optimal solution of scheduling. Finally, illustrative examples are given to verify the feasibility and effectiveness of the proposed method. Compared with the existing virtual wafer method, this method can effectively reduce the system cycle time and improve the production efficiency of dual-arm cluster tools with chamber cleaning.

关键词： Semiconductor device modeling Gases Job shop scheduling Process control Semiconductor device manufacture System recovery linear programming Robot sensing systems Throughput Cleaning

An Almost Feasible Sequential linear programming Algorithm

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Kiessling, David Vanaret, Charlie Astudillo, Alejandro Decré, Wilm Swevers, Jan MECO Research Team Dept. of Mechanical Engineering KU Leuven Flanders Make@KU Leuven Leuven3001 Belgium Mathematical Algorithmic Intelligence Division Zuse-Institut Berlin Berlin Germany

This paper proposes an almost feasible Sequential linear programming (afSLP) algorithm. In the first part, the practical limitations of previously proposed Feasible Sequential linear programming (FSLP) methods are discussed along with illustrative examples. Then, we present a generalization of FSLP based on a tolerance-tube method that addresses the shortcomings of FSLP. The proposed algorithm afSLP consists of two phases. Phase I starts from random infeasible points and iterates towards a relaxation of the feasible set. Once the tolerance-tube around the feasible set is reached, phase II is started and all future iterates are kept within the tolerance-tube. The novel method includes enhancements to the originally proposed tolerance-tube method that are necessary for global convergence. afSLP is shown to outperform FSLP and the state-of-the-art solver IPOPT on a SCARA robot optimization problem. Copyright © 2024, The Authors. All rights reserved.

关键词： linear programming