• 제목/요약/키워드: SOS optimization

검색결과 6건 처리시간 0.021초

Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization

  • Tejani, Ghanshyam G.;Savsani, Vimal J.;Patel, Vivek K.
    • Journal of Computational Design and Engineering
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    • 제3권3호
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    • pp.226-249
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    • 2016
  • The symbiotic organisms search (SOS) algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.

Improved Hybrid Symbiotic Organism Search Task-Scheduling Algorithm for Cloud Computing

  • Choe, SongIl;Li, Bo;Ri, IlNam;Paek, ChangSu;Rim, JuSong;Yun, SuBom
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3516-3541
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    • 2018
  • Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

Symbiotic organisms search algorithm based solution to optimize both real power loss and voltage stability limit of an electrical energy system

  • Pagidi, Balachennaiah;Munagala, Suryakalavathi;Palukuru, Nagendra
    • Advances in Energy Research
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    • 제4권4호
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    • pp.255-274
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    • 2016
  • This paper presents a novel symbiotic organisms search (SOS) algorithm to optimize both real power loss (RPL) and voltage stability limit (VSL) of a transmission network by controlling the variables such as unified power flow controller (UPFC) location, UPFC series injected voltage magnitude and phase angle and transformer taps simultaneously. Mathematically, this issue can be formulated as nonlinear equality and inequality constrained multi objective, multi variable optimization problem with a fitness function integrating both RPL and VSL. The symbiotic organisms search (SOS) algorithm is a nature inspired optimization method based on the biological interactions between the organisms in ecosystem. The advantage of SOS algorithm is that it requires a few control parameters compared to other meta-heuristic algorithms. The proposed SOS algorithm is applied for solving optimum control variables for both single objective and multi-objective optimization problems and tested on New England 39 bus test system. In the single objective optimization problem only RPL minimization is considered. The simulation results of the proposed algorithm have been compared with the results of the algorithms like interior point successive linear programming (IPSLP) and bacteria foraging algorithm (BFA) reported in the literature. The comparison results confirm the efficacy and superiority of the proposed method in optimizing both single and multi objective problems.

THE DOMAIN OF ATTRACTION FOR A SEIR EPIDEMIC MODEL BASED ON SUM OF SQUARE OPTIMIZATION

  • Chen, Xiangyong;Li, Chunji;Lu, Jufang;Jing, Yuanwei
    • 대한수학회보
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    • 제49권3호
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    • pp.517-528
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    • 2012
  • This paper is estimating the domain of attraction for a class of susceptible-exposed-infectious-recovered (SEIR) epidemic dynamic models by using sum of squares optimization. First, the stability is analyzed for the equilibriums of SEIR model, and the domain of attraction in the endemic equilibrium is estimated by using sum of squares optimization. Finally, a numerical example is examined.

Canola Oil로부터 코코아버터와 유사한 Triacylglycerol 조성을 가진 재구성지질의 효소적 합성 최적화 연구 (Optimization of Lipase-Catalyzed Production of Structured Lipids from Canola Oil Containing Similar Composition of Triacylglycerols to Cocoa Butter)

  • 문준희;이정희;신정아;홍순택;이기택
    • 한국식품영양과학회지
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    • 제40권10호
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    • pp.1430-1437
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    • 2011
  • 본 연구에서는 카놀라유(canola oil)를 이용하여 코코아버터 유사 재구성지질 합성의 최적조건을 연구하였다. 반응기질로는 카놀라유와 palmitic ethyl ester와 stearic ethyl ester를 이용하였으며, 효소는 Lipozyme TLIM을 사용하여 반응기질의 몰비율과 반응효소의 양, 반응시간을 독립변수로 하고, D-optimal 계획에 의한 반응표면분석에 따라 합성을 실시하였다. 반응을 통해 acyl-migration은 최소로 일어나며, POS 및 SOS, POP의 함량은 최대로 합성되는 조건을 최적화 조건으로 결정하였다. D-optimal 계획에 의한 반응표면분석을 실행한 결과, sn-2 위치 지방산 조성의 변화를 일으키는 acyl-migration($Y_1$)은 최소로 일어나고 POS($Y_2$)와 SOS($Y_3$), POP($Y_4$)는 최대로 일어나는 조건은 기질의 몰비율은 canola oil : palmitic ethyl ester : stearic ethyl ester=1:3:9이며, 반응효소의 양은 6%이고, 반응시간은 40 min이었다. 이와 같은 반응조건으로 합성된 재구성지질의 acylmigration(% of palmitic acid+stearic acid, $Y_1$)은 10.43%, POS($Y_2$)의 함량은 25.31%, SOS($Y_3$)는 19.79%, 그리고 POP($Y_4$)는 11.22%로 측정되었다.

반응표면분석법에 의한 1-Palmitoyl-2-Oleoyl-3-Oleoyl Glycerol과 1-Palmitoyl-2-Oleoyl-3-Palmitoyl Glycerol의 아세톤 분별 공정 최적화 (Optimization of Acetone-Fractionation for 1-Palmitoyl-2-Oleoyl-3-Oleoyl Glycerol and 1-Palmitoyl-2-Oleoyl-3-Palmitoyl Glycerol by Response Surface Methodology)

  • 신정아;성민혜;이선모;손정매;이정희;홍순택;이기택
    • 한국식품영양과학회지
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    • 제40권7호
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    • pp.975-980
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    • 2011
  • 팜 스테아린으로부터 분별온도($X_1$=25, 30, $35^{\circ}C$)와 팜 스테아린에 대한 아세톤의 비율($X_2$=1:3, 1:6, 1:9, w/v)을 요인 변수로 하여 중심합성계획에 의한 반응표면분석을 이용하여 최적화한 POP purity($Y_1$, %), POO purity($Y_2$, %), POO+POP의 content($Y_3$, g)의 조건을 살펴보았다. $Y_1$, $Y_2$, $Y_3$의 종속요인들을 모두 최대화하면서 순도를 가장 높일 수 있는 분별조건을 예측한 결과, 분별온도 $29.3^{\circ}C$에서 팜 스테아린에 대한 사용 아세톤의 비율이 1:5.7일 경우 60.9%의 POP와 23.8%의 POO를 함유한 POO와 POP 분별유를 4 g의 팜 스테아린에서 3.0 g(75% 수율)의 획득을 예측할 수 있었다. POO와 POP의 순도를 높이면서 함량을 높이는 최적화 조건의 검증을 위하여 반복실험을 수행한 결과, POP purity와 POO purity, POO+POP의 content는 각각 60.18%, 24.10%, 74.38%(2.97 g)로, 반복 실험 간에 유의적인 차이가 없음을 확인하였다. 이렇게 얻어진 POO와 POP 함량 및 순도가 높은 유지는 앞으로 CBE의 주된 대칭형 TAG(POS와 SOS) 합성에 이용될 수 있을 것으로 사료된다.