Multi-constrained Polarity Optimization of Large-scale FPRM Circuits Based on Multi-objective Discrete Particle Swarm Optimization

FU Qiang; WANG Pengjun; TONG Nan; WANG Mingbo; ZHANG Huihong

doi:10.11999/JEIT160458

Volume 39 Issue 3

Mar. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(3): 717-723

FU Qiang, WANG Pengjun, TONG Nan, WANG Mingbo, ZHANG Huihong. Multi-constrained Polarity Optimization of Large-scale FPRM Circuits Based on Multi-objective Discrete Particle Swarm Optimization[J]. Journal of Electronics & Information Technology, 2017, 39(3): 717-723. doi: 10.11999/JEIT160458

Citation:

FU Qiang, WANG Pengjun, TONG Nan, WANG Mingbo, ZHANG Huihong. Multi-constrained Polarity Optimization of Large-scale FPRM Circuits Based on Multi-objective Discrete Particle Swarm Optimization[J]. Journal of Electronics & Information Technology, 2017, 39(3): 717-723. doi: 10.11999/JEIT160458

Citation:

FU Qiang, WANG Pengjun, TONG Nan, WANG Mingbo, ZHANG Huihong. Multi-constrained Polarity Optimization of Large-scale FPRM Circuits Based on Multi-objective Discrete Particle Swarm Optimization[J]. Journal of Electronics & Information Technology, 2017, 39(3): 717-723. doi: 10.11999/JEIT160458

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Multi-constrained Polarity Optimization of Large-scale FPRM Circuits Based on Multi-objective Discrete Particle Swarm Optimization

doi: 10.11999/JEIT160458

1.
2.
(Institute of Circuits and Systems, Ningbo University, Ningbo 315211, China)

Funds:

The National Natural Science Foundation of China (61306041, 61234002), The Twelfth Five-Year Plan of Zhejiang Province Key Discipline (Computer Application Technology), The Scientific Research Fund of Zhejiang Provincial Education Department (Y201326770), The Ningbo Natural Science Foundation (2014A610069, 2015A610107)

Received Date: 2016-05-05
Rev Recd Date: 2016-10-18
Publish Date: 2017-03-19

Abstract

Abstract

For multi-constrained polarity optimization of large-scale FPRM circuits, a Multi-Objective Discrete Particle Swarm Optimization (MODPSO) algorithm is proposed. Firstly, the multi-objective decision model is established according to the delay-area trade-off of large-scale FPRM circuits. Secondly, combined with tabular technique and MODPSO, the best polarities of delay and area are searched for large-scale FPRM circuits, to obtain the Pareto optimal set for delay and area. Finally, the algorithm MODPSO is compared with the algorithm DPSO and NSGA-II on MCNC Benchmarks with PLA format, and the results verify the effectiveness of the MODPSO.
- FPRM circuits,
- Delay-area trade-off,
- Polarity search,
- Pareto,
- Multi-Objective Discrete Particle Swarm Optimization (MODPSO)

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References(21)

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