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基于MODPSO算法的FPRM電路多約束極性?xún)?yōu)化方法

符強(qiáng),  汪鵬君,  童楠,  王銘波,  張會(huì)紅

符強(qiáng), 汪鵬君, 童楠, 王銘波, 張會(huì)紅. 基于MODPSO算法的FPRM電路多約束極性?xún)?yōu)化方法[J]. 電子與信息學(xué)報(bào), 2017, 39(3): 717-723. doi: 10.11999/JEIT160458
引用本文: 符強(qiáng), 汪鵬君, 童楠, 王銘波, 張會(huì)紅. 基于MODPSO算法的FPRM電路多約束極性?xún)?yōu)化方法[J]. 電子與信息學(xué)報(bào), 2017, 39(3): 717-723. doi: 10.11999/JEIT160458
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

基于MODPSO算法的FPRM電路多約束極性?xún)?yōu)化方法

doi: 10.11999/JEIT160458
  • 2.

    (寧波大學(xué)電路與系統(tǒng)研究所 寧波 315211) ②(寧波大學(xué)科學(xué)技術(shù)學(xué)院 寧波 315212)

基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(61306041, 61234002)，十二五浙江省高校重點(diǎn)學(xué)科計(jì)算機(jī)應(yīng)用技術(shù)，浙江省教育廳科研項(xiàng)目(Y201326770)，寧波市自然科學(xué)基金(2014A610069，2015A610107)

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

  • 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)

  • 摘要: 為求解較大規(guī)模FPRM邏輯電路中多約束條件下的極性?xún)?yōu)化問(wèn)題，該文提出一種基于多目標(biāo)離散粒子群優(yōu)化(Multi-Objective Discrete Particle Swarm Optimization, MODPSO)算法的求解方法。首先針對(duì)FPRM電路極性設(shè)計(jì)需要滿足延時(shí)短、面積小的多約束要求，構(gòu)建了多目標(biāo)決策模型。然后結(jié)合極性轉(zhuǎn)換算法和MODPSO算法，對(duì)電路進(jìn)行最優(yōu)極性搜索，以獲取電路延時(shí)和面積的Pareto最優(yōu)解集。最后利用17個(gè)MCNC Benchmark電路進(jìn)行測(cè)試，并將MODPSO算法與DPSO算法、NSGA-II算法進(jìn)行實(shí)驗(yàn)對(duì)比，結(jié)果驗(yàn)證了算法的有效性。
    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.
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出版歷程
  • 收稿日期:  2016-05-05
  • 修回日期:  2016-10-18
  • 刊出日期:  2017-03-19

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