Search Results - subject:"Genetic Algorithm (GA)"

Design optimization and analysis of a biomass gasification based BCHP system: A case study in Harbin, China

Wang, Jiang-Jiang; Xu, Zi-Long; Jin, Hong-Guang; Shi, … - In: Renewable Energy 71 (2014) C, pp. 572-583

hybrid cooling system is optimized to minimize the annual total cost (ATC) by the genetic algorithm (GA). Then, the energetic …

Persistent link: https://www.econbiz.de/10010906494

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

Dizqah, Arash M.; Maheri, Alireza; Busawon, Krishna - In: Renewable Energy 72 (2014) C, pp. 212-222

employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior …

Persistent link: https://www.econbiz.de/10010930865

Optimal economic designing of grid-connected photovoltaic systems with multiple inverters using linear and nonlinear module models based on Genetic Algorithm

Bakhshi, Reza; Sadeh, Javad; Mosaddegh, Hamid-Reza - In: Renewable Energy 72 (2014) C, pp. 386-394

much necessary. In this paper, a new intelligent-based approach is proposed to design GCPV systems using Genetic Algorithm … (GA). By defining the net present value (NPV) of system as the objective function and considering electrical constraints …

Persistent link: https://www.econbiz.de/10010930868

Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems

Sanaye, Sepehr; Khakpaay, Navid - In: Energy 72 (2014) C, pp. 145-158

Energy, economic, and environmental analyses of combined cooling, heating and power (CCHP) systems were performed here to select the nominal capacities of gas engines by combination of optimization algorithm and maximum rectangle method (MRM). The analysis was performed for both priority of...

Persistent link: https://www.econbiz.de/10011055071

A combined dispatching criteria approach to scheduling dual flow-shops

Chiou, Chie-wun; Chen, Wen-min; Wu, Muh-cherng - In: International journal of production research 51 (2013) 3, pp. 927-939

Persistent link: https://www.econbiz.de/10009689265

Using response surface design to determine the optimal parameters of genetic algorithm and a case study

Kucukkoc, Ibrahim; Karaoglan, Aslan Deniz; Yaman, Ramazan - In: International journal of production research 51 (2013) 17, pp. 5039-5054

Persistent link: https://www.econbiz.de/10010193843

An integrated framework for risk response planning under resource constraints in large engineering projects

Fang, Chao; Marle, Franck; Xie, Min; Zio, Enrico - In: IEEE transactions on engineering management : EM 60 (2013) 3, pp. 627-639

Persistent link: https://www.econbiz.de/10009784805

Application of genetic algorithm for solving optimum power flow problems

Vennila, H.; Prakash, T. Ruban Deva; Malini, B. G.; … - In: International journal of information systems and supply … 6 (2013) 2, pp. 62-71

Persistent link: https://www.econbiz.de/10010128212

Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm

Xi, Huan; Li, Ming-Jia; Xu, Chao; He, Ya-Ling - In: Energy 58 (2013) C, pp. 473-482

algorithm (GA) is chosen as a novel way to determine the optimal fractions of the flow rates in regenerative ORC systems. The …-stage regenerative ORC (DRORC) system using six different working fluids under the same waste heat condition are examined. The genetic …

Persistent link: https://www.econbiz.de/10010811825

A comparative study of optimal hybrid methods for wind power prediction in wind farm of Alberta, Canada

Bigdeli, Nooshin; Afshar, Karim; Gazafroudi, Amin Shokri; … - In: Renewable and Sustainable Energy Reviews 27 (2013) C, pp. 20-29

comparative study is carried out among neural networks trained by imperialist competitive algorithm (ICA), genetic algorithm (GA …

Persistent link: https://www.econbiz.de/10010703025