Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY

Diego Ricardo Cajachagua Guerreros; Sario Angel Chamorro Quijano; Felipe Nestor Gutarra Meza

doi:10.1007/978-3-031-64359-0_38

Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY

Diego Ricardo Cajachagua Guerreros, Sario Angel Chamorro Quijano, Felipe Nestor Gutarra Meza

Research output: Chapter in Book/Report › Conference contribution › peer-review

Abstract

The research focuses on the development of a fuzzy model using X-Fuzzy to evaluate optimal ready-mix concrete suppliers. In collaboration with five supply chain specialists, company requirements and supplier capabilities are analyzed to develop a comprehensive analysis sheet. The mathematical model is based on fuzzy logic and uses X-FUZZY software to numerically evaluate optimal suppliers, considering sixteen input variables, their interrelationships and corresponding inference rules. The X-Fuzzy tool allows the generation of a fuzzy neural network, developed through continuous learning and iterative modification. The results show that the application of X-Fuzzy streamlines and improves decision making, simplifying the selection of the most suitable supplier. The model highlights the importance of key variables and suggests continuously evaluating the fuzzy logic model to adapt to emerging technologies and methodologies. In conclusion, the X-Fuzzy fuzzy model offers a dynamic approach to evaluate suppliers in the ready-mix concrete context, allowing dynamic decision making and considering multiple factors and variations based on a fuzzy model.

Original language	American English
Title of host publication	Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers
Editors	Shuliang Li
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	485-499
Number of pages	15
ISBN (Print)	9783031643583
DOIs	https://doi.org/10.1007/978-3-031-64359-0_38
State	Indexed - 2024
Externally published	Yes
Event	10th International Conference on Information Management, ICIM 2024 - Cambridge, United Kingdom Duration: 8 Mar 2024 → 10 Mar 2024

Publication series

Name	Communications in Computer and Information Science
Volume	2102 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	10th International Conference on Information Management, ICIM 2024
Country/Territory	United Kingdom
City	Cambridge
Period	8/03/24 → 10/03/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

Fuzzy model
Fuzzy Neural Network
Supply chains
X-Fuzzy

Access to Document

10.1007/978-3-031-64359-0_38

Cite this

Guerreros, D. R. C., Quijano, S. A. C., & Meza, F. N. G. (2024). Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY. In S. Li (Ed.), Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers (pp. 485-499). (Communications in Computer and Information Science; Vol. 2102 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-64359-0_38

Guerreros, Diego Ricardo Cajachagua ; Quijano, Sario Angel Chamorro ; Meza, Felipe Nestor Gutarra. / Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY. Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. editor / Shuliang Li. Springer Science and Business Media Deutschland GmbH, 2024. pp. 485-499 (Communications in Computer and Information Science).

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title = "Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY",

abstract = "The research focuses on the development of a fuzzy model using X-Fuzzy to evaluate optimal ready-mix concrete suppliers. In collaboration with five supply chain specialists, company requirements and supplier capabilities are analyzed to develop a comprehensive analysis sheet. The mathematical model is based on fuzzy logic and uses X-FUZZY software to numerically evaluate optimal suppliers, considering sixteen input variables, their interrelationships and corresponding inference rules. The X-Fuzzy tool allows the generation of a fuzzy neural network, developed through continuous learning and iterative modification. The results show that the application of X-Fuzzy streamlines and improves decision making, simplifying the selection of the most suitable supplier. The model highlights the importance of key variables and suggests continuously evaluating the fuzzy logic model to adapt to emerging technologies and methodologies. In conclusion, the X-Fuzzy fuzzy model offers a dynamic approach to evaluate suppliers in the ready-mix concrete context, allowing dynamic decision making and considering multiple factors and variations based on a fuzzy model.",

keywords = "Fuzzy model, Fuzzy Neural Network, Supply chains, X-Fuzzy",

author = "Guerreros, {Diego Ricardo Cajachagua} and Quijano, {Sario Angel Chamorro} and Meza, {Felipe Nestor Gutarra}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 10th International Conference on Information Management, ICIM 2024 ; Conference date: 08-03-2024 Through 10-03-2024",

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doi = "10.1007/978-3-031-64359-0_38",

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Guerreros, DRC , Quijano, SAC & Meza, FNG 2024, Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY. in S Li (ed.), Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. Communications in Computer and Information Science, vol. 2102 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 485-499, 10th International Conference on Information Management, ICIM 2024, Cambridge, United Kingdom, 8/03/24. https://doi.org/10.1007/978-3-031-64359-0_38

Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY. / Guerreros, Diego Ricardo Cajachagua ; Quijano, Sario Angel Chamorro; Meza, Felipe Nestor Gutarra.
Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. ed. / Shuliang Li. Springer Science and Business Media Deutschland GmbH, 2024. p. 485-499 (Communications in Computer and Information Science; Vol. 2102 CCIS).

Research output: Chapter in Book/Report › Conference contribution › peer-review

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AU - Guerreros, Diego Ricardo Cajachagua

AU - Quijano, Sario Angel Chamorro

AU - Meza, Felipe Nestor Gutarra

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - The research focuses on the development of a fuzzy model using X-Fuzzy to evaluate optimal ready-mix concrete suppliers. In collaboration with five supply chain specialists, company requirements and supplier capabilities are analyzed to develop a comprehensive analysis sheet. The mathematical model is based on fuzzy logic and uses X-FUZZY software to numerically evaluate optimal suppliers, considering sixteen input variables, their interrelationships and corresponding inference rules. The X-Fuzzy tool allows the generation of a fuzzy neural network, developed through continuous learning and iterative modification. The results show that the application of X-Fuzzy streamlines and improves decision making, simplifying the selection of the most suitable supplier. The model highlights the importance of key variables and suggests continuously evaluating the fuzzy logic model to adapt to emerging technologies and methodologies. In conclusion, the X-Fuzzy fuzzy model offers a dynamic approach to evaluate suppliers in the ready-mix concrete context, allowing dynamic decision making and considering multiple factors and variations based on a fuzzy model.

AB - The research focuses on the development of a fuzzy model using X-Fuzzy to evaluate optimal ready-mix concrete suppliers. In collaboration with five supply chain specialists, company requirements and supplier capabilities are analyzed to develop a comprehensive analysis sheet. The mathematical model is based on fuzzy logic and uses X-FUZZY software to numerically evaluate optimal suppliers, considering sixteen input variables, their interrelationships and corresponding inference rules. The X-Fuzzy tool allows the generation of a fuzzy neural network, developed through continuous learning and iterative modification. The results show that the application of X-Fuzzy streamlines and improves decision making, simplifying the selection of the most suitable supplier. The model highlights the importance of key variables and suggests continuously evaluating the fuzzy logic model to adapt to emerging technologies and methodologies. In conclusion, the X-Fuzzy fuzzy model offers a dynamic approach to evaluate suppliers in the ready-mix concrete context, allowing dynamic decision making and considering multiple factors and variations based on a fuzzy model.

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BT - Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers

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Y2 - 8 March 2024 through 10 March 2024

ER -

Guerreros DRC , Quijano SAC, Meza FNG. Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY. In Li S, editor, Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2024. p. 485-499. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-64359-0_38

Fuzzy Logic Model for the Evaluation of the Optimal Ready-Mixed Concrete Supplier Using a Fuzzy Neural Network in X-FUZZY

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this