Control and Optimization in Applied Mathematics

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Multi-Objective Optimization Problem Involving Max-Product Fuzzy Relation Inequalities with Application in Wireless Communication

Articles in Press

Document Type : Research Article

Authors

1 Department of Applied Mathematics‎, ‎University of Mazandaran‎, ‎Babolsar‎, ‎Iran.

2 Department of Mathematics‎, Payame Noor University (PNU)‎, P.O‎. ‎Box 19395-4697‎, ‎Tehran‎, ‎Iran‎.

10.30473/coam.2025.72543.1270

Abstract

This paper explores a specific category of optimization management models tailored for wireless communication systems‎. ‎To enhance the efficiency of managing these systems‎, ‎we introduce a fuzzy relation multi-objective programming approach‎. ‎We define the concept of a feasible index set and present a novel algorithm‎, ‎termed the feasible index set algorithm‎, ‎which is designed to determine the optimal lexicographic solution to the problem‎, ‎demonstrating polynomial computational complexity‎. ‎Previous studies have indicated that the emission base stations within wireless communication systems can be effectively modeled using a series of fuzzy relation inequalities through max-product composition‎. ‎This topic is also addressed in our paper‎. ‎ ‎Wireless communication is widely employed across various sectors‎, ‎encompassing mobile communication and data transmission‎. ‎In this framework‎, ‎information is transmitted via electromagnetic waves generated by fixed emission base stations‎.

Highlights

  • This study addresses a distinct category of optimization management models specifically tailored for wireless communication systems.
  • A novel fuzzy relation multi-objective programming approach is proposed to enhance the efficiency of managing complex communication systems.
  • The concept of a feasible index set is established, serving as a foundational element for the problem formulation.
  • A new algorithm termed the Feasible Index Set Algorithm, is developed to efficiently identify the best lexicographic solution within the optimization framework.
  • The proposed algorithm operates with polynomial computational complexity, ensuring practicality and efficiency in real-world applications.

Keywords

Main Subjects

References
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Control and Optimization in Applied Mathematics

Articles in Press, Accepted Manuscript
Available Online from 13 April 2025
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