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JACIII Vol.23 No.2 pp. 293-299
doi: 10.20965/jaciii.2019.p0293
(2019)

Paper:

Application of Decision Making Algorithm for Green Electromechanical Product Design Optimization

Yi Zhang*,** and Qinghui Meng*,***

*School of Mechanical and Electrical Engineering, Henan Polytechnic Institute
No.666 Kongming Road, Nanyang, Henan 473000, China

**School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology
200 Xiaolingwei, Nanjing 210094, China

***School of Control Engineering, Henan University of Science And Technology
No.666 Kongming Road, Nanyang, Henan 473000, China

Received:
May 18, 2018
Accepted:
August 20, 2018
Published:
March 20, 2019
Keywords:
green electromechanical products, optimization algorithm, entropy weight method, analytic hierarchy process, EW&AHP fusion technology
Abstract

Green products are considered to be the only way for human beings to follow the strategy of sustainable development. They have become one of the hotspots of modern design, manufacture and consumption. A green design method of electromechanical products based on case-based reasoning is presented in this paper. This paper puts forward and uses a “EW&AHP fusion technology” to scientifically determine the index weight, and uses multi target decision-making method to design the index system, establish the evaluation optimization algorithm model of green electromechanical product design scheme, and comprehensively evaluate and optimize the green product design scheme from the aspects of economy, technology and green. Sort, provide decision support for production and operation of related enterprises. The results show that the algorithm can not only give full play to the role of the data itself, but also fully reflect the green requirements of the green electromechanical products, and also give consideration to the profit goal of the enterprise.

Cite this article as:
Y. Zhang and Q. Meng, “Application of Decision Making Algorithm for Green Electromechanical Product Design Optimization,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.2, pp. 293-299, 2019.
Data files:
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Last updated on Nov. 04, 2024