Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing
The selection of a demand forecasting method is critical for companies aiming to avoid manufacturing overproduction or shortages in pursuit of sustainable development. Various qualitative and quantitative criteria with different weights must be considered during the evaluation of a forecasting metho...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-09-01
|
| Series: | Axioms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1680/12/10/926 |
| _version_ | 1797574751902760960 |
|---|---|
| author | Ta-Chung Chu Thi Bich Ha Nghiem |
| author_facet | Ta-Chung Chu Thi Bich Ha Nghiem |
| author_sort | Ta-Chung Chu |
| collection | DOAJ |
| description | The selection of a demand forecasting method is critical for companies aiming to avoid manufacturing overproduction or shortages in pursuit of sustainable development. Various qualitative and quantitative criteria with different weights must be considered during the evaluation of a forecasting method. The qualitative criteria and criteria weights are usually assessed in linguistic terms. Aggregating these various criteria and linguistic weights for evaluating and selecting demand forecasting methods in sustainable manufacturing is a major challenge. This paper proposes an extension of fuzzy elimination and choice translating reality (ELECTRE) I to resolve this problem. In the proposed method, fuzzy weighted ratings are defuzzified with the signed distance to develop a crisp ELECTRE I model. Moreover, an extension to ELECTRE I is developed by suggesting an extended modified discordance matrix and a closeness coefficient for ranking alternatives. The proposed extension can overcome the problem of information loss, which can lead to incorrect ranking results when using the Hadamard product to combine concordance and modified discordance matrices. A comparison is conducted to show the advantage of the proposed extension. Finally, a numerical example is used to demonstrate the feasibility of the proposed method. Furthermore, a numerical comparison is made to display the advantage of the proposed method. |
| first_indexed | 2024-03-10T21:26:47Z |
| format | Article |
| id | doaj.art-c3c53315c12f439c9cfd57f2198995bb |
| institution | Directory Open Access Journal |
| issn | 2075-1680 |
| language | English |
| last_indexed | 2024-03-10T21:26:47Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Axioms |
| spelling | doaj.art-c3c53315c12f439c9cfd57f2198995bb2023-11-19T15:38:01ZengMDPI AGAxioms2075-16802023-09-01121092610.3390/axioms12100926Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable ManufacturingTa-Chung Chu0Thi Bich Ha Nghiem1Department of Industrial Management and Information, Southern Taiwan University of Science and Technology, Tainan City 710301, TaiwanSchool of Business, International University—Vietnam National University, Ho Chi Minh City 70000, VietnamThe selection of a demand forecasting method is critical for companies aiming to avoid manufacturing overproduction or shortages in pursuit of sustainable development. Various qualitative and quantitative criteria with different weights must be considered during the evaluation of a forecasting method. The qualitative criteria and criteria weights are usually assessed in linguistic terms. Aggregating these various criteria and linguistic weights for evaluating and selecting demand forecasting methods in sustainable manufacturing is a major challenge. This paper proposes an extension of fuzzy elimination and choice translating reality (ELECTRE) I to resolve this problem. In the proposed method, fuzzy weighted ratings are defuzzified with the signed distance to develop a crisp ELECTRE I model. Moreover, an extension to ELECTRE I is developed by suggesting an extended modified discordance matrix and a closeness coefficient for ranking alternatives. The proposed extension can overcome the problem of information loss, which can lead to incorrect ranking results when using the Hadamard product to combine concordance and modified discordance matrices. A comparison is conducted to show the advantage of the proposed extension. Finally, a numerical example is used to demonstrate the feasibility of the proposed method. Furthermore, a numerical comparison is made to display the advantage of the proposed method.https://www.mdpi.com/2075-1680/12/10/926demand forecasting methodsfuzzy ELECTRE Iextended modified discordance matrixHadamard productcloseness coefficient |
| spellingShingle | Ta-Chung Chu Thi Bich Ha Nghiem Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing Axioms demand forecasting methods fuzzy ELECTRE I extended modified discordance matrix Hadamard product closeness coefficient |
| title | Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing |
| title_full | Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing |
| title_fullStr | Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing |
| title_full_unstemmed | Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing |
| title_short | Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing |
| title_sort | extension of fuzzy electre i for evaluating demand forecasting methods in sustainable manufacturing |
| topic | demand forecasting methods fuzzy ELECTRE I extended modified discordance matrix Hadamard product closeness coefficient |
| url | https://www.mdpi.com/2075-1680/12/10/926 |
| work_keys_str_mv | AT tachungchu extensionoffuzzyelectreiforevaluatingdemandforecastingmethodsinsustainablemanufacturing AT thibichhanghiem extensionoffuzzyelectreiforevaluatingdemandforecastingmethodsinsustainablemanufacturing |