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Journal of Information and Optimization Sciences cover

Journal of Information and Optimization Sciences

(Since 1980)
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Journal of Information and Optimization Sciences
Open Access Research Article

Exploring fuzzy assignment dynamics : A computational journey with ‘R’

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pp. 815–829Vol. 46Issue 3April 2025DOI: 10.47974/JIOS-1835XML
Received:
12 Mar 2024
Published Online:
05 Feb 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1835
Pages:
815–829

Abstract

Fuzzy logic, with its ability to model uncertainty and imprecision, offers a promising avenue for addressing complex decision-making processes in various domains of information technology. This paper presents a computational exploration of fuzzy assignment dynamics using the statistical computing language ‘R’. Through a series of case studies and practical implementations, we delve into the application of fuzzy logic principles in decision support systems, pattern recognition, natural language processing, control systems, data mining, optimization, human-computer interaction, and robotics. Leveraging the flexibility and robustness of ‘R’, we demonstrate how fuzzy assignment techniques can enhance the adaptability and intelligence of computational systems in handling uncertain environments. By examining real-world scenarios and employing ‘R’ as a computational tool, this journey offers insights into the practical implications and potential advancements in fuzzy logic applications within the realm of information technology. The proposed algorithm is applicable to any finite number of sources for a balanced fuzzy assignment problem.

Keywords

Computing environmentAssignment problemFuzzy assignment problem (FAP)Triangular fuzzy numberOpen-source programming language

Subject Classifications

94D0590C0590C08

References

[1] C. Thangapandi, “Solving Fuzzy Assignment Problem in a New Method using Robust Ranking Procedure,” International Journal of Advanced Research in Engineering and Technology, vol. 11, no. 2, pp. 361-368 (2020). 
[2] T. A. Thakre, O. K. Chaudhari and R. Gupta, “Comparison of effectiveness of models for solving fuzzy assignment problem,” in International Conference on Research Frontiers in Sciences, NA (2021). 
[3] M. Muamer, “Fuzzy Assignment problems,” Journal of Science, vol. 10, no. 1, pp. 40-47, August (2020). 
[4] P. Malini and M. Ananthanarayanan, “Solving Fuzzy Assignment Problem using Ranking of Generalized Trapezoidal Fuzzy Numbers,” Indian Journals of Science and Technology, vol. 9, no. 20, May (2016). 
[5] R. Leelambari, S. Anupriya, S. Revathi and S. Venkatesh, “A Novel Method for the Fuzzy Assignment Problem Using SBD Technique,” European Chemical Bulletin, vol. 12, no. 9, pp. 601-611 (2023).
[6] P. S. Kumar, “Intuitionistic fuzzy solid assignment problems: a software-based approach,” International Journal of System Assurance Engineering and Management, vol. 10, no. 1, p. 661–675, May 2019. 
[7] B. Hayat, K. H. Kim and K.-I. Kim, “A study on fuzzy logic based cloud computing,” Cluster Computing, vol. 21, no. 1, p. 589–603 (2018). 
[8] D. Gurukumaresan, C. Duraisamy, R. Srinivasan and V. Vijayan, “Optimal solution of fuzzy assignment problem with centroid methods,” Materials Today: Proceedings, vol. 37, no. 2, pp. 553-555 (2021). 
[9] S. Dhouib and T. Sutikno, “Solving the trapezoidal fuzzy assignment problem using the novel Dhouib-Matrix-AP1 heuristic,” Bulletin of Electrical Engineering and Informatics, vol. 12, no. 2, pp. 950-957, April (2023). 
[10] J. Bhadauria, S. Kumar, D. Kumar and A. Kumari, “Distinctive representations of icosagonal fuzzy numbers along with novel defuzzification techniques for solving fuzzy assignment problems,” Pre Print, vol. 1, no. 1, pp. 1-32, August (2023). 
[11] A. Khandelwal and A. Kumar, “An Advanced Approach to the Employee Recruitment Process through Genetic Algorithm,” International Journal of Information Technology, vol. 13, no. 1, pp. 313-319 , February (2021). 
[12] A. Khandelwal, A. Kumar and M. Gupta, “Triangular Fuzzy Assignment Problems for Solving Amalgamated Computing System,” International Conference on Computational Performance Evaluation, North-Eastern Hill University, Shillong, pp. 348-353, 1-3 Dec (2021).
[13] A. Khandelwal and A. Agarwal, “An Amalgamated Approach of Fuzzy Logic and Genetic Algorithm for Better Recruitment Process,” Transactions of Networks and Communications (TNC) , vol. 3, no. 3, pp. 23-31, June (2015). 
[14] A. Khandelwal and A. Kumar, “Evaluation of Service Time in DCS using Fuzzy and Clustering Technique,” in International Conference on Computational Performance Evaluation (ComPE 2020), Shilong (2020). 
[15] A. Khandelwal, “Fuzzy based Amalgamated Technique for Optimal Service Time in Distributed Computing System,” International Journal of Recent Technology and Engineering, vol. 8, no. 3, pp. 6763-6768, September (2019). 
[16] M. Venkatachalapathy, P. Nagarajan and A. Jayaraja, “An Optimal Solution for Solving Unbalanced Assignment Problems Using Triangular Fuzzy Numbers,” International Journal of Advanced Science and Technology, vol. 29, no. 6, pp. 4107 – 4114 (2020).
[17] A. Khandelwal, S. Saxena and A. Kumar. “’KSK’ Algorithm for Optimizing DCS Performance using ‘R’”, International Conference on Soft Computing for Problem Solving - SocProS 2023, Lecture Notes in Networks and Systems by Springer, vol. 994, pp. 33-46, July (2024).
[18] S. Tilva and J. Dhodiya, “Multi-Objective Assignment Problem Solved by Hybrid Jaya Algorithm,” Journal of Interdisciplinary Mathematics, vol. 25, no. 1, pp. 109–121, January (2022).

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