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Solution for the optimality of an intuitionistic fuzzy redundancy allocation problem for complex system using Yager’s ranking method of defuzzification with soft computation

Author

Listed:
  • Rajesh Paramanik

    (Sidho-Kanho-Birsha University)

  • Nirmal Kumar

    (The University of Burdwan)

  • Sanat Kumar Mahato

    (Sidho-Kanho-Birsha University)

Abstract

Reliability optimization is of high concern in the field of system design, communication, industry etc. The reliability of a system can be maximized in several ways leading to different types of reliability optimization problems like, redundancy allocation problem (RAP), reliability redundancy allocation problem (RRAP). The RAP type of problems require suitable allocations to maximize the system reliability under certain restrictions. We have considered the RAP type problem in crisp environment and also the imprecise model of it is designed to explain the uncertainties of the model. In this paper, a real coded elitist genetic algorithm is employed for solving the redundancy allocation problem of a complicated system in intuitionistic fuzzy environment. All the control parameters of the system are considered as triangular intuitionistic fuzzy numbers. To crispify the different parameters of constrained intuitionistic fuzzy optimization problem, Yager’s ranking method of crispification is applied. The Big-M penalty technique is utilized to convert the constrained optimization problem into the unconstrained one. Finally, some numerical experiments are performed to maximize the system reliabilities for optimal component reliabilities. The sensitivity studies with respect to the GA parameters are presented graphically.

Suggested Citation

  • Rajesh Paramanik & Nirmal Kumar & Sanat Kumar Mahato, 2022. "Solution for the optimality of an intuitionistic fuzzy redundancy allocation problem for complex system using Yager’s ranking method of defuzzification with soft computation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 615-624, April.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:2:d:10.1007_s13198-021-01314-5
    DOI: 10.1007/s13198-021-01314-5
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    References listed on IDEAS

    as
    1. Sanat Kumar Mahato & Nabaranjan Bhattacharyee & Rajesh Pramanik, 2020. "Fuzzy reliability redundancy optimisation with signed distance method for defuzzification using genetic algorithm," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 37(3), pages 307-323.
    2. Anuj Kumar & Sangeeta Pant & Mangey Ram & Shshank Chaube, 2019. "Multi-objective grey wolf optimizer approach to the reliability-cost optimization of life support system in space capsule," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 276-284, April.
    3. Ali Salmasnia & Sadegh Noori & Hadi Mokhtari, 2019. "A redundancy allocation problem by using utility function method and ant colony optimization: tradeoff between availability and total cost," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 416-428, June.
    4. Amalendu Singha Mahapatra & Hardik N Soni & Maheswar Singha Mahapatra & Biswajit Sarkar & Sanat Majumder, 2021. "A Continuous Review Production-Inventory System with a Variable Preparation Time in a Fuzzy Random Environment," Mathematics, MDPI, vol. 9(7), pages 1-27, March.
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