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Hardness of Online Sleeping Combinatorial Optimization Problems [article]

Satyen Kale and Chansoo Lee and Dávid Pál
2016 arXiv   pre-print
We show that several online combinatorial optimization problems that admit efficient no-regret algorithms become computationally hard in the sleeping setting where a subset of actions becomes unavailable  ...  The hardness result for the sleeping version of the Online Shortest Paths problem resolves an open problem presented at COLT 2015 (Koolen et al., 2015).  ...  For clarity, we define an online combinatorial optimization problem as a family of instances of online combinatorial optimization (and correspondingly for online sleeping combinatorial optimization).  ... 
arXiv:1509.03600v3 fatcat:o3w62rvyg5a6xiv4xlh3eboq4a

Scheduling (Dagstuhl Seminar 20081)

Nicole Megow, David Shmoys, Ola Svensson
2020 Dagstuhl Reports  
The seminar focused on the interplay between scheduling problems and problems that arise in the management of transportation and traffic.  ...  This report documents the program and the outcomes of Dagstuhl Seminar 20081 "Scheduling".  ...  The authors present a way to transform instances of 1|r j , d j | j p j U j into instances of P 2|prec|C max , and show that an o(log n)-level Sherali-Adams lift does not lead to a (1 + ) approximation  ... 
doi:10.4230/dagrep.10.2.50 dblp:journals/dagstuhl-reports/MegowSS20 fatcat:dtrzez6ogbhdjc56hbnv3hyuhy

Sleeping Combinatorial Bandits [article]

Kumar Abhishek, Ganesh Ghalme, Sujit Gujar, Yadati Narahari
2021 arXiv   pre-print
In this paper, we study an interesting combination of sleeping and combinatorial stochastic bandits.  ...  An algorithm can select a subset of arms from the \emph{availability set} (sleeping bandits) and receive the corresponding reward along with semi-bandit feedback (combinatorial bandits).  ...  This problem, even when the qualities of the base arms are known, is known to be NP-hard in general [WN99].  ... 
arXiv:2106.01624v1 fatcat:qhi6xxtd7rftneev2bwj2dsooi

Online optimization of wireless sensors selection over an unknown stochastic environment

Muhammad Anjum Qureshi, Wardah Sarmad, Hira Noor, Ali Hassan Mirza
2018 2018 26th Signal Processing and Communications Applications Conference (SIU)  
We propose an online combinatorial optimization algorithm based on multi-armed bandits framework that learns the expected best subset of sensors, and the regret of the proposed online algorithm is sub-linear  ...  The constraints to this optimization are the battery power of the sensor and number of sensors that are active at a given time.  ...  CONCLUSION In this paper, we propose an online combinatorial optimization algorithm for wireless sensors to provide desired coverage in a particular area.  ... 
doi:10.1109/siu.2018.8404570 dblp:conf/siu/QureshiSNM18 fatcat:alhnosvjbrb3lncsdkak2ouccu

Green ICT for Rural Development

Sangita B. Phunde, Madhuri Godbole, Supriya G. Sapa
2016 IBMRD s Journal of Management & Research  
Use non conventional sources of energy can be a good solution to remove electricity problem.  ...  The objective of this study is to find an effective solution for the above mentioned problems to apply Green ICT for rural development.  ...  International J o u r n a l o f Combinatorial Optimization Problems and Informatics, Vol. 2, No. 3, Sep-Dec 2011, ISSN: 2007-1558 , pp. 39-51. Ayesha Anam, A. S.  ... 
doi:10.17697/ibmrd/2016/v5i1/88681 fatcat:fffiwwm3brgsrkwbnm5uogntra

Target Coverage and Network Connectivity Challenges in Wireless Sensor Networks

Deepa R, Revathi Venkataraman
2018 EAI Endorsed Transactions on Energy Web  
Secondly, the set cover approach plays a major role in solving target coverage problem which group sensors into each cover set thereby, target coverage was achieved.  ...  issues and open research challenges are addressed by classifying the approaches available in literature into three broad categories namely, adaptable coverage radius, coverage deployment strategy, and sleep  ...  a Target Coverage and Network Connectivity Challenges in Wireless Sensor Networks problem of combinatorial optimization.  ... 
doi:10.4108/eai.13-7-2018.165674 fatcat:kux6u65ohbc2bgaw3nlw7dgjku

COURSE SCHEDULING ACCORDING TO STUDENT STRESS

Shuai Ma, Ali Akgunduz, Yong Zeng
2015 Proceedings of the Canadian Engineering Education Association (CEEA)  
In this paper, the quantification of course difficulty and student stress is discussed, followed by a student stress model which can integrate student stress into the course scheduling problem.  ...  The low retention rate for students, especially engineering students, is a widespread problem.  ...  COURSE SCHEDULING ALGORITHM Course scheduling problem, or university course timetabling problem (UCTP), is a classic combinatorial problem with NP-hard, which means with the problem size growing, the time  ... 
doi:10.24908/pceea.v0i0.5849 fatcat:6rcvfrc6fjd2bgvnt7y5b4xofi

Combinatorial Sleeping Bandits with Fairness Constraints [article]

Fengjiao Li, Jia Liu, Bo Ji
2019 arXiv   pre-print
To that end, we propose a new Combinatorial Sleeping MAB model with Fairness constraints, called CSMAB-F, aiming to address the aforementioned crucial modeling issues.  ...  To tackle this new problem, we extend an online learning algorithm, UCB, to deal with a critical tradeoff between exploitation and exploration and employ the virtual queue technique to properly handle  ...  In particular, integrating fairness constraints adds a new layer of difficulty to the combinatorial sleeping MAB problem that is already quite challenging.  ... 
arXiv:1901.04891v3 fatcat:fhkab4htenfjvgk323dxlunwoy

Improved Sleeping Bandits with Stochastic Actions Sets and Adversarial Rewards [article]

Aadirupa Saha, Pierre Gaillard, Michal Valko
2020 arXiv   pre-print
In this paper, we consider the problem of sleeping bandits with stochastic action sets and adversarial rewards.  ...  We then study the most general version of the problem where at each round available sets are generated from some unknown arbitrary distribution (i.e., without the independence assumption) and propose an  ...  Hardness of online sleeping combinatorial optimization problems. In Advances in Neural Information Processing Systems, pp. 2181-2189, 2016. Kanade, V. and Steinke, T.  ... 
arXiv:2004.06248v2 fatcat:rk45lxboszbd7nswyqf3ezrrmq

Joint placement and sleep scheduling of grid-connected solar powered road side units in vehicular networks

Vageesh D.C., Moumita Patra, C. Siva Ram Murthy
2014 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)  
Taking these into account, we aim to perform optimal placement of RSUs with sleep scheduling where RSUs are powered by conventional grid and solar power.  ...  A direction orthogonal to it is sleep scheduling of RSUs to minimize their energy consumption.  ...  Since, multi-criteria knapsack is NP-hard [15] , the given problem is also NP-hard. Hence, we use a heuristic Rainbow Product Ranking algorithm to get the near optimal solution in polynomial time.  ... 
doi:10.1109/wiopt.2014.6850343 dblp:conf/wiopt/CPM14 fatcat:ubtwu7x5tjgv3dgpgag4okssde

Approximation Modeling for the Online Performance Management of Distributed Computing Systems

Dara Kusic, Nagarajan Kandasamy, Guofei Jiang
2007 Fourth International Conference on Autonomic Computing (ICAC'07)  
For an online optimization scheme to be of practical value in a distributed setting, however, it must successfully tackle the curses of dimensionality and modeling.  ...  A promising method of automating management tasks in computing systems is to formulate them as control or optimization problems in terms of performance metrics.  ...  hard disk.  ... 
doi:10.1109/icac.2007.8 dblp:conf/icac/KusicKJ07 fatcat:qherds355vbnhpykrb2dkizpfy

Approximation Modeling for the Online Performance Management of Distributed Computing Systems

D. Kusic, N. Kandasamy, Guofei Jiang
2008 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
For an online optimization scheme to be of practical value in a distributed setting, however, it must successfully tackle the curses of dimensionality and modeling.  ...  A promising method of automating management tasks in computing systems is to formulate them as control or optimization problems in terms of performance metrics.  ...  hard disk.  ... 
doi:10.1109/tsmcb.2008.925756 pmid:18784008 fatcat:nppi3dfmofferj354oer2uktam

A Survey of Virtual Machine Placement Techniques in a Cloud Data Center

Zoha Usmani, Shailendra Singh
2016 Procedia Computer Science  
Many of the recently proposed techniques realize dynamic consolidation while optimizing the VM placement.  ...  Energy consumption of massive-scale cloud data centers is increasing unacceptably.  ...  , as a contrast to mathematical approaches, to solve complex combinatorial problem of optimal VM placement.  ... 
doi:10.1016/j.procs.2016.02.093 fatcat:yrgmosxvszgv7jjc4vmyycksta

Metaheuristics for dynamic combinatorial optimization problems

S. Yang, Y. Jiang, T. T. Nguyen
2012 IMA Journal of Management Mathematics  
Many real-world optimization problems are combinatorial optimization problems subject to dynamic environments.  ...  In such dynamic combinatorial optimization problems (DCOPs), the objective, decision variables, and/or constraints may change over time, and so solving DCOPs is a challenging task.  ...  Introduction In our daily life, we face various optimization problems, of which many are combinatorial optimization problems (COPs).  ... 
doi:10.1093/imaman/dps021 fatcat:krc3pa24rnb3phdh2bayzcz6ui

Resource Allocation Using Gradient Boosting Aided Deep Q-Network for IoT in C-RANs [article]

Yifan Luo, Jiawei Yang, Wei Xu, Kezhi Wang, Marco Di Renzo
2019 arXiv   pre-print
(GBDT) to approximate the solutions of second order cone programming (SOCP) problem.  ...  We demonstrate that the generated policy is error-tolerant even the gradient boosting regression may not be strictly subject to the constraints of the original problem.  ...  RELATED WORKS The resource allocation problem under C-RANs is normally interpreted into an optimization problem, where one needs to search the decision space to find an optimal combinatorial set of decisions  ... 
arXiv:1910.13084v1 fatcat:hghsr4ovwzfm3paygzirxxqwgi
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