A Multi-objective Fuzzy Optimization Method of Resource Input Based on Genetic Algorithm
With the increasing complexity of engineering
problems, the traditional, single-objective and deterministic
optimization method can not meet people-s requirements. A
multi-objective fuzzy optimization model of resource input is built for
M chlor-alkali chemical eco-industrial park in this paper. First, the
model is changed into the form that can be solved by genetic algorithm
using fuzzy theory. And then, a fitness function is constructed for
genetic algorithm. Finally, a numerical example is presented to show
that the method compared with traditional single-objective
optimization method is more practical and efficient.
[1] Xiaoli Zhang, Jianqiang Yang, Chunying Chang, Wei Dong,
"Multi-objective fuzzy optimization method and its practical application
to engineering design," Journal of Dalian University of Technology, vol.
45, pp. 374-378, 2005.
[2] Yong Liao, "Study on evolutionary algorithm for fuzzy multi-objective
optimization problems," Wuhan University, 2003.
[3] Toshihiko Nakata, "Energy-economic models and the environment,"
Progress in Energy and Combustion Science, vol. 30, pp. 417-475, 2004.
[4] Baoding Liu, Introduction to Uncertain Programming, Beijing: Tsinghua
University, 2005.
[5] Hun Kuk, Tetsuzo Tanino and Masahiro Tanaka, "Sensitivity Analysis in
Parametrized Convex Vector Optimization," Journal of Mathematical
Analysis and Applications, vol. 202, pp. 501-524, 1996.
[1] Xiaoli Zhang, Jianqiang Yang, Chunying Chang, Wei Dong,
"Multi-objective fuzzy optimization method and its practical application
to engineering design," Journal of Dalian University of Technology, vol.
45, pp. 374-378, 2005.
[2] Yong Liao, "Study on evolutionary algorithm for fuzzy multi-objective
optimization problems," Wuhan University, 2003.
[3] Toshihiko Nakata, "Energy-economic models and the environment,"
Progress in Energy and Combustion Science, vol. 30, pp. 417-475, 2004.
[4] Baoding Liu, Introduction to Uncertain Programming, Beijing: Tsinghua
University, 2005.
[5] Hun Kuk, Tetsuzo Tanino and Masahiro Tanaka, "Sensitivity Analysis in
Parametrized Convex Vector Optimization," Journal of Mathematical
Analysis and Applications, vol. 202, pp. 501-524, 1996.
@article{"International Journal of Earth, Energy and Environmental Sciences:53603", author = "Tao Zhao and Xin Wang", title = "A Multi-objective Fuzzy Optimization Method of Resource Input Based on Genetic Algorithm", abstract = " With the increasing complexity of engineering
problems, the traditional, single-objective and deterministic
optimization method can not meet people-s requirements. A
multi-objective fuzzy optimization model of resource input is built for
M chlor-alkali chemical eco-industrial park in this paper. First, the
model is changed into the form that can be solved by genetic algorithm
using fuzzy theory. And then, a fitness function is constructed for
genetic algorithm. Finally, a numerical example is presented to show
that the method compared with traditional single-objective
optimization method is more practical and efficient.", keywords = "Fitness function, genetic algorithm, multi-objectivefuzzy optimization, satisfaction degree membership function.", volume = "4", number = "9", pages = "408-5", }