Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises

A supplier, multi-objective technology, applied in manufacturing computing systems, commerce, data processing applications, etc., can solve problems such as poor generalizability, poor optimization effect, and neglect of combination relationships.

Inactive Publication Date: 2016-06-08
BEIFANG UNIV OF NATITIES
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Problems solved by technology

[0004] For the selection of parts suppliers of bearing manufacturing enterprises, the current evaluation method is mainly based on the quantification and weighting calculation of specific indicators, but different bearing manufacturing enterprises have obvious differences in the degree of attention to the evaluation indicators of parts suppliers, this method is only applicable For a specific type of bearing manufacturing enterprise, the generalizability is poor; when index weighting, a single weight or the average of multiple weights

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  • Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises
  • Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises
  • Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises

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Embodiment Construction

[0047] Describe the present invention below in conjunction with specific embodiment:

[0048] In this embodiment, the purchased part of a certain bearing manufacturing enterprise is a certain type of roller, and there are 3 suppliers of this part, A, B, and C. It is necessary to perform multi-objective optimization on these 3 roller suppliers, and select 1 Home is the best supplier.

[0049] Step 1: According to the decomposition of the overall goal of the selection of parts suppliers of bearing manufacturing enterprises, establish an evaluation index system, namely {Index 1 , Index 2 ,...,Index 5}, which in turn correspond to quality indicators (sub-objectives), supply capacity indicators (sub-objectives), economic status indicators (sub-objectives), cooperative service indicators (sub-objectives) and environmental impact indicators (sub-objectives);

[0050] Step 2: Obtain the ability of each expert from the historical samples through the neural network training method: ...

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Abstract

The invention provides a part supplier multi-target preferable selection method orienting bearing manufacturing enterprises. The degree of capacity of each expert is acquired from historical samples through a neural network training method by considering objective difference of the experience levels and the knowledge levels of different experts; the degree of capacity of the experts is introduced and then a multi-order fuzzy rough set integrated analytic hierarchy process with combination of an analytic hierarchy process in which fuzzy numbers replace accurate numbers and rough sets is provided so that combined processing of multiple experts for multiple part suppliers on the score result of a single indicator is realized; a multi-weight information integration model is established, and integration weights of the evaluation indicators are solved; and the part suppliers are ranked according to the indicator value of each evaluation indicator and the integration weights of the indicators of multiple part suppliers, and the optimal part supplier is obtained.

Description

[0001] 1. Field [0002] The invention relates to the field of supplier selection in enterprise supply chain management, in particular to a multi-objective optimization method for parts suppliers oriented to bearing manufacturing enterprises. 2. Background technology [0003] Bearings are mainly composed of rollers, rings, sealing rings, cages, dust covers and other parts. With the increasingly fierce market competition, bearing manufacturers are increasingly concentrating on their core business, while external suppliers provide a large number of parts, such as balls, sealing rings, etc. These purchased parts have a direct impact on the quality of finished products, how to optimize parts suppliers has become the key for bearing manufacturers to improve their market competitiveness. [0004] For the selection of parts suppliers of bearing manufacturing enterprises, the current evaluation method is mainly based on the quantification and weighting calculation of specific indicat...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06Q50/04G06Q30/06
CPCG06Q30/0609G06Q50/04G06N3/043G06N3/042Y02P90/30
Inventor 李联辉穆春阳高宗池高阳朱德馨丁少虎雷婷卢龙高杨郝宇
Owner BEIFANG UNIV OF NATITIES
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