TY  - JOUR
AV  - none
TI  - Multiobjective design optimization of a nano-CMOS voltage-controlled oscillator using game theoretic-differential evolution
SP  - 293
N1  - cited By 18
SN  - 15684946
PB  - Elsevier Ltd
EP  - 299
KW  - Algorithms; Circuit oscillations; Decision making; Evolutionary algorithms; Game theory; Integrated circuit design; Optimization; Oscillistors; Particle swarm optimization (PSO); Variable frequency oscillators
KW  -  Differential Evolution; Evolutionary game theory; Hypervolume indicators; Meta heuristic algorithm; Multi objective; Multi-objective design optimization; Nano CMOS; Scalarization approach
KW  -  Multiobjective optimization
ID  - scholars5901
N2  - Engineering problems presenting themselves in a multiobjective setting have become commonplace in most industries. In such situations the decision maker (DM) requires several solution options prior to selecting the best or the most attractive solution with respect to the current industrial circumstances. The weighted sum scalarization approach was employed in this work in conjunction with three metaheuristic algorithms: particle swarm optimization (PSO), differential evolution (DE) and the improved DE algorithm (GTDE) (which was enhanced using ideas from evolutionary game theory). These methods are then used to generate the approximate Pareto frontier to the nano-CMOS voltage-controlled oscillator (VCO) design problem. Some comparative studies were then carried out to compare the proposed method as compared to the standard DE approach. Examination on the quality of the solutions across the Pareto frontier obtained using these algorithms was carried out using the hypervolume indicator (HVI). © 2015 Elsevier B.V. All rights reserved.
Y1  - 2015///
VL  - 32
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927917967&doi=10.1016%2fj.asoc.2015.03.016&partnerID=40&md5=4eaebc0df9689e0d68aa4ea729e1e38b
JF  - Applied Soft Computing Journal
A1  - Ganesan, T.
A1  - Elamvazuthi, I.
A1  - Vasant, P.
ER  -