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High Performance Computing for Cyber Physical Social Systems by Using Evolutionary Multi-Objective Optimization Algorithm
Abstract
Cyber-physical social systems (CPSS) is an emerging complicated topic which is a combination of cyberspace, physical space, and social space. Many problems in CPSS can be mathematically modelled as optimization problems, and some of them are multi-objective optimization (MOO) problems (MOPs). In general, the MOPs are difficult to solve by traditional mathematical programming methods. High performance computing with much faster speed is required to address these issues. In this paper, a kind of high performance computing approaches, evolutionary multi-objective optimization (EMO) algorithms, is used to deal with these MOPs. A floorplanning case study is presented to demonstrate the feasibility of our proposed approach. B*-tree and a multistep simulated annealing (MSA) algorithm are cooperatively used to solve this case. As per experimental results for this case, the proposed method is well capable of searching for feasible floorplan solutions, and it can reach 74.44 percent (268/360) success rates for floorplanning problems.
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Medhi, I., Patnaik, S., Brunskill, E., Gautama, S. N. N., Thies, W., & Toyama, K. (2011) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1959022.1959024 · Cited by 285
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Cai, X., Niu, Y., Geng, S., Zhang, J., Cui, Z., Li, J., & Chen, J. (2020) · Concurrency and Computation: Practice and Experience · doi:10.1002/cpe.5478 · Cited by 267
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Metadata
- Authors
- Wang, G.-G., Cai, X., Cui, Z., Min, G., & Chen, J.
- Venue
- IEEE Transactions on Emerging Topics in Computing
- Published
- 2017
- Pages
- 1-1
- ISSN
- 2168-6750 (ISSN-L)
- OpenAlex
- W2616346973
- Cited by
- 194
- References
- 1
- FWCI
- 25.33
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, G.-G., Cai, X., Cui, Z., Min, G., & Chen, J. (2017). High Performance Computing for Cyber Physical Social Systems by Using Evolutionary Multi-Objective Optimization Algorithm. IEEE Transactions on Emerging Topics in Computing. https://doi.org/10.1109/tetc.2017.2703784
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