Journal
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
Volume 8, Issue 1, Pages 20-30Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETC.2017.2703784
Keywords
Optimization; High performance computing; Computational modeling; Mathematical model; Adaptation models; Robot sensing systems; Computer architecture; Cyber-physical social systems; high performance computing; evolutionary multi-objective optimization; floorplanning; multistep simulated annealing
Funding
- Natural Science Foundation of Jiangsu Province [BK20150239]
- National Natural Science Foundation of China [61503165, 61673196, 61402207]
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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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