Survey on Fuzzy Logic and Subjective Performance Evaluation of Supply Chain Management

Authors

  • Lidia Shanthi  Lecturer, Department Electrical Engineering Samara University Ethiopia
  • Bizuayehu Bogale  Dean, Department Electrical Engineering Samara University Ethiopia
  • Milky Ali  HOD, Department Electrical Engineering Lecturer Samara University Ethiopia

Keywords:

Supply Chain, Performance Measurement, qualitative measures and fuzzy logic

Abstract

Fuzzy logic can be a capable apparatus for directors to use rather than customary numerical models while assessing the execution of supply chains. The adaptability of the model enables the leader to present unclearness, vulnerability, and subjectivity into the assessment framework. In this paper we study an elective technique for the execution assessment framework rather than the conventional quantitative strategies. Execution assessments speak to a fundamentally critical choice that regularly includes subjective data. Models and heuristic systems that attention on the utilization of various kinds of data are accessible; in any case, with couple of special cases, the models are not sufficiently strong to be connected in a viable, authoritatively helpful way. Fuzzy logic models give a sensible answer for these basic choice circumstances. After broad investigation of the writing, we suggest a result of investigating Fuzzy logic approach in assessing subjective parts of execution of inventory network administration. In this paper we overview fuzzy logic as a powerful and simple understanding technique to assess subjective parts of execution of supply chains.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Lidia Shanthi, Bizuayehu Bogale, Milky Ali, " Survey on Fuzzy Logic and Subjective Performance Evaluation of Supply Chain Management" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.636-642, March-April-2018.