The computation time of the exact and optimal solution to the set covering problem increases exponentially concerning the problem size due to an exhaustive search for the solution. We propose a novel GPU-based paralle...
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Landscape analysis has received increasing attention in the literature, with a major focus on producing feature data to be used in a machine learning pipeline for automatic algorithm selection and configuration. In co...
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The generational model maintaining both parent and offspring populations is frequently employed for designing multi-objective evolutionary algorithms. The archive population of non-dominated solutions acquired during ...
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We study repeated first-price auctions and general repeated Bayesian games between two players, where one player, the learner, employs a no-regret learning algorithm, and the other player, the optimizer, knowing the l...
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Numerous real-world applications involve complex many-objective optimization problems characterized by a large number of objective functions. Despite the development of various algorithms to address this kind of probl...
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Factor Analysis is about finding a low-rank plus sparse additive decomposition from a noisy estimate of the signal covariance matrix. In order to get such a decomposition, we formulate an optimization problem using th...
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Given the limitations of traditional line loss assessment methods in terms of learning efficiency and prediction accuracy, this study chose the 10kV medium voltage distribution network as the research objective. After...
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This research presents a new & integrated method to tackle the difficulties in distribution planning (DSP). It does this including distributed generation(DG), which promise in areas controlled by distribution util...
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We study the steady-state Nash equilibrium-seeking problem for sampled-data games with LTI dynamics and quadratic costs. The key challenge is to guarantee the robust stability and convergence properties of the closed-...
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ISBN:
(纸本)9781713872344
We study the steady-state Nash equilibrium-seeking problem for sampled-data games with LTI dynamics and quadratic costs. The key challenge is to guarantee the robust stability and convergence properties of the closed-loop system in the presence of local individual sampling mechanisms assigned to each of the players in the game. This problem is non-trivial due to the unstable behaviors that can arise when sequential control updates (rather than parallel) emerge in the closed-loop system because of the existence of local control triggering mechanisms in each node of the network. To address this issue, we introduce a controls framework based on tools from hybrid dynamical systems theory. Our results are illustrated via numerical examples. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)
Microservice architecture (MSA) is a paradigm to design and develop scalable distributed applications using loosely coupled, highly cohesive components that can be deployed independently. The applications that realize...
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Microservice architecture (MSA) is a paradigm to design and develop scalable distributed applications using loosely coupled, highly cohesive components that can be deployed independently. The applications that realize the MSA may contain thousands of services that together form the overall system. Microservices interact with each other by producing and consuming data. Deploying frequently communicating services to the same physical resource would reduce network utilization, which is vital for reducing costs and improving scalability. Since the physical resources have limited capacity, it is not always possible to deploy communicating services to the same resource. Therefore, automated efficient deployment alternatives need to be generated for MSA in the design phase. To address this problem, we proposed an algorithmic approach to generate efficient microservice deployment configurations to available cloud resources in our previous study. In this study, a tool (Micro-IDE) has been proposed to realize and evaluate this approach. The Micro-IDE tool has been validated using a case study inspired by the Spotify application.
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