High Performance Computing for Cyber Physical Social Systems by Using Evolutionary Multi-Objective Optimization Algorithm

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 gen...

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Bibliographic Details
Published in:IEEE transactions on emerging topics in computing 2020-01, Vol.8 (1), p.20-30
Main Authors: Wang, Gai-Ge, Cai, Xingjuan, Cui, Zhihua, Min, Geyong, Chen, Jinjun
Format: Article
Language:English
Subjects:
Adaptation models
Computation
Computational modeling
Computer architecture
Computer simulation
Cyber-physical social systems
Evolutionary algorithms
evolutionary multi-objective optimization
Feasibility
floorplanning
Floorplans
High performance computing
Internet
Mathematical model
Mathematical programming
Mopping
Multiple objective analysis
multistep simulated annealing
Optimization
Robot sensing systems
Simulated annealing
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Summary: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.
ISSN:2168-6750
2168-6750
DOI:10.1109/TETC.2017.2703784