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Implementing an appropriate maintenance policy would help us to have a more reliable system and reduce the total costs. In this paper, a dynamic maintenance plan is proposed for repairable multi-component systems, where each component is…

Systems and Control · Electrical Eng. & Systems 2020-01-27 Nooshin Yousefi , Stamatis Tsianikas , Jian Zhou , David W. Coit

This paper deals with the problem of preventive maintenance (PM) scheduling of pipelines subject to external corrosion defects. The preventive maintenance strategy involves an inspection step at some epoch, together with a repair schedule.…

Data Structures and Algorithms · Computer Science 2016-10-06 Assia Boumahdaf , Michel Broniatowski

Most memories suffer from both permanent defects and intermittent random errors. The partitioned linear block codes (PLBC) were proposed by Heegard to efficiently mask stuck-at defects and correct random errors. The PLBC have two separate…

Information Theory · Computer Science 2014-12-11 Yongjune Kim , B. V. K. Vijaya Kumar

A robust positioning pattern is a large array that allows a mobile device to locate its position by reading a possibly corrupted small window around it. In this paper, we provide constructions of binary positioning patterns, equipped with…

Information Theory · Computer Science 2020-01-01 Yeow Meng Chee , Duc Tu Dao , Han Mao Kiah , San Ling , Hengjia Wei

One of the grand challenges of Mathematics instruction is to provide students with problems that are both accessible and have a reasonably elegant solution. Instructors commonly resort to resources like course textbooks, online-learning…

History and Overview · Mathematics 2024-02-13 Ryan H. Allaire , Margaret Reynolds , Andrew C. Lee

We consider the line planning problem in public transport in the Parametric City, an idealized model that captures typical scenarios by a (small) number of parameters. The Parametric City is rotation symmetric, but optimal line plans are…

Optimization and Control · Mathematics 2022-01-25 Berenike Masing , Niels Lindner , Ralf Borndörfer

We consider nonlinear optimization problems that involve surrogate models represented by neural networks. We demonstrate first how to directly embed neural network evaluation into optimization models, highlight a difficulty with this…

Optimization and Control · Mathematics 2021-11-23 Dominic Yang , Prasanna Balaprakash , Sven Leyffer

Many learning algorithms are formulated in terms of finding model parameters which minimize a data-fitting loss function plus a regularizer. When the regularizer involves the l0 pseudo-norm, the resulting regularization path consists of a…

Machine Learning · Computer Science 2020-03-06 Toby Hocking , Joseph Vargovich

The structural design process for buildings is time-consuming and laborious. To automate this process, structural engineers combine optimization methods with simulation tools to find an optimal design with minimal building mass subject to…

Machine Learning · Computer Science 2020-08-14 Kai-Hung Chang , Chin-Yi Cheng

While mixture of linear regressions (MLR) is a well-studied topic, prior works usually do not analyze such models for prediction error. In fact, {\em prediction} and {\em loss} are not well-defined in the context of mixtures. In this paper,…

Machine Learning · Statistics 2022-05-27 Avishek Ghosh , Arya Mazumdar , Soumyabrata Pal , Rajat Sen

Large language models (LLMs) are powerful tools but are often expensive to deploy at scale. LLM query routing mitigates this by dynamically assigning queries to models of varying cost and quality to obtain a desired trade-off. Prior query…

A major issue of locally repairable codes is their robustness. If a local repair group is not able to perform the repair process, this will result in increasing the repair cost. Therefore, it is critical for a locally repairable code to…

Information Theory · Computer Science 2019-04-09 Ali Tebbi , Terence H. Chan , Chi Wan Sung

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous…

Optimization and Control · Mathematics 2024-06-28 Pol Puigdemont , Stratis Skoulakis , Grigorios Chrysos , Volkan Cevher

Linearized models of power systems are often desirable to formulate tractable control and optimization problems that still reflect real-world physics adequately under various operating conditions. In this paper, we propose an approach that…

Optimization and Control · Mathematics 2018-05-28 Marc Hohmann , Joseph Warrington , John Lygeros

Many problems of interest for cyber-physical network systems can be formulated as Mixed Integer Linear Programs in which the constraints are distributed among the agents. In this paper we propose a distributed algorithm to solve this class…

Optimization and Control · Mathematics 2017-12-06 Andrea Testa , Alessandro Rucco , Giuseppe Notarstefano

The benefits of transmission line switching are well-known in terms of reducing operational cost and improving system reliability of power systems. However, finding the optimal power network configuration is a challenging task due to the…

Optimization and Control · Mathematics 2022-12-26 Santanu S. Dey , Burak Kocuk , Nicole Redder

In spite of extended recent interest in System Reliability-Based Design Optimization (System RBDO) and life-cycle cost or Risk Optimization (RO), there is a lack of published studies on optimal design of redundant hyperstatic systems with…

Computational Engineering, Finance, and Science · Computer Science 2022-01-26 Andre T. Beck

The partner units problem (PUP) is an acknowledged hard benchmark problem for the Logic Programming community with various industrial application fields like surveillance, electrical engineering, computer networks or railway safety systems.…

Artificial Intelligence · Computer Science 2013-10-18 Erich Christian Teppan , Gerhard Friedrich

The redundancy allocation problem is formulated minimizing the design cost for a series-parallel system with multiple component choices whereas ensuring a given system reliability level. The obtained model is a nonlinear integer programming…

Optimization and Control · Mathematics 2012-03-16 F. Castro , J. Gago , I. Hartillo , J. Puerto , J. M. Ucha

Solving mixed-integer optimization problems with embedded neural networks with ReLU activation functions is challenging. Big-M coefficients that arise in relaxing binary decisions related to these functions grow exponentially with the…

Optimization and Control · Mathematics 2025-02-06 Christoph Plate , Mirko Hahn , Alexander Klimek , Caroline Ganzer , Kai Sundmacher , Sebastian Sager