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A Collective Neurodynamic Approach to Survivable Virtual Network Embedding
2018
International Journal of Advanced Computer Science and Applications
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In this paper, a collective neurodynamic approach has been proposed to reduce amount of provisioned redundant resources and reduce cost of embedding virtual networks. ...
One of the commonly applied mechanisms to protect against such failures is provisioning redundant substrate resources for each virtual network to be used to recover affected virtual resources. ...
ACKNOWLEDGMENT The authors would like to express their cordial thanks to the department of Research and Development (R&D) of IMAM, university for research grant no: 370903. ...
doi:10.14569/ijacsa.2018.090309
fatcat:vusfmjx7mfhg5aqyoul4sm2bi4
A Review of Path-Planning Approaches for Multiple Mobile Robots
2022
Machines
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Numerous path-planning studies have been conducted in past decades due to the challenges of obtaining optimal solutions. ...
The decision-making strategies mainly consist of centralized and decentralized approaches. The trend of the decision-making system is to move towards a decentralized planner. ...
It first addresses AGV resource allocation and transportation tasks, and then solves the transportation scheduling problem [80] . ...
doi:10.3390/machines10090773
fatcat:bojo6szg7jcqzkipleoxj4e3qi
Combined Economic Emission Dispatch of Microgrid with the Incorporation of Renewable Energy Sources Using Improved Mayfly Optimization Algorithm
2022
Computational Intelligence and Neuroscience
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A combined cost optimization approach is examined to minimize operational cost and emission levels while satisfying the load demand of the microgrid. ...
The main objective of this paper is to elucidate the combined economic emission dispatch CEED problem in the microgrid to attain optimal generation cost. ...
Acknowledgments e authors wish to thank the Hindustan Institute of Technology & Science, Chennai, and Vellore Institute of Technology, Chennai Campus, for their support and encouragement to carry out this ...
doi:10.1155/2022/6461690
pmid:35479598
pmcid:PMC9038389
fatcat:unwugcg4qfbmzdcbbyi52ewype
Accelerated Primal-Dual Mirror Dynamics for Centrailized and Distributed Constrained Convex Optimization Problems
[article]
2022
arXiv
pre-print
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Then, we extend APDMD into two distributed dynamical approaches to deal with two types of distributed smooth optimization problems, i.e., distributed constrained consensus problem (DCCP) and distributed ...
This paper investigates two accelerated primal-dual mirror dynamical approaches for smooth and nonsmooth convex optimization problems with affine and closed, convex set constraints. ...
The corresponding inertial dynamical approach is then extended to solve the distributed optimization problems. ...
arXiv:2205.15983v2
fatcat:ekybkayblrfsjmyno7embhfppm
2021 Index IEEE Transactions on Cybernetics Vol. 51
2021
IEEE Transactions on Cybernetics
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Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
., +, TCYB July 2021 3524-3534 A Novel Multiagent Neurodynamic Approach to Constrained Distributed Convex Optimization. ...
Deng, C., +, TCYB April 2021 1812-1821 A Novel Multiagent Neurodynamic Approach to Constrained Distributed Convex Optimization. ...
doi:10.1109/tcyb.2021.3139447
fatcat:myjx3olwvfcfpgnwvbuujwzyoi
Patterns, predictions, and actions: A story about machine learning
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2102.05242v1 fatcat:ghg6hn4djvdszkwpkg37lul5nm
A chapter on datasets as benchmarks examines their histories and scientific bases. ...
Self-contained introductions to causality, the practice of causal inference, sequential decision making, and reinforcement learning equip the reader with concepts and tools to reason about actions and ...
However, ERM is a special optimization problem, and its structure enables nonconvexity to enter in a graceful way. ...
arXiv:2102.05242v2
fatcat:wy47g4fojnfuxngklyewtjtqdi
Crawler
[chapter]
2009
Encyclopedia of Database Systems
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As a result, it is common (at the time of writing) for data accesses to RAM to require several hundred CPU cycles to resolve. ...
For such workloads, improving the locality of data-intensive operations can have a direct impact on the system's overall performance. ...
It should be noted that optimizing E is a combinatorial problem that is NP-Complete and thus any practical algorithm to optimize it cannot guarantee optimality. ...
doi:10.1007/978-0-387-39940-9_2315
fatcat:x4qspjdytvhvroc7h753dihp7u
The Parametric Cost Function Approximation: A new approach for multistage stochastic programming
[article]
2022
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We present the idea of a parameterized deterministic optimization model, and in particular a deterministic lookahead model, as a powerful strategy for many complex stochastic decision problems. ...
The most common approaches for solving multistage stochastic programming problems in the research literature have been to either use value functions ("dynamic programming") or scenario trees ("stochastic ...
We hope that the thoughts in this paper encourage the stochastic optimization community to include parameterized deterministic models as valid policies for stochastic optimization problems. ...
doi:10.48550/arxiv.2201.00258
fatcat:tc5zf4tnijhxfly2vwlu4sa54i
Review of distributed control and optimization in energy internet: From traditional methods to artificial intelligence‐based methods
2021
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Traditional control and optimization methods often have limited effectiveness in solving these problems. ...
The purpose of this study is to provide a reference as well as useful research ideas for the study of EI control systems. ...
However, there are still some limitations in solving nonconvex and nonlinear problems. ...
doi:10.17863/cam.70924
fatcat:debb4wza6nbzjampibrikgd2eu
50 Algebra in Computational Complexity (Dagstuhl Seminar 14391) Manindra Agrawal, Valentine Kabanets, Thomas Thierauf, and Christopher Umans 85 Privacy and Security in an Age of Surveillance (Dagstuhl Perspectives Workshop
unpublished
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We present a framework for applying the one-shot approach also to optimal control problems with unsteady Navier-Stokes equations. ...
The application of the adjoint model is a common approach for high dimensional optimization problems, however often a continuous approach instead of a discrete one is used. ...
What metrics should be optimized? ...
fatcat:e5wnf6cuhvc3bceegijgut34zm