Determining the optimal maintenance period in order to minimize the life cycle cost and maximize the performance and reliability index of the bridge

Document Type : Original Article

Authors

1 PhD student, Construction engineering and management, Islamic Azad University, Qeshm international Branch

2 Assistant Professor, Department of civil engineering, Islamic Azad University, Chaloos Branch

3 Assistant professor, Pardisan University of Fereydonkenar, Fereydonkenar, Iran

Abstract

Population growth and development of economic relations have led to increase utilization of transportation infrastructures. The bridge is one of the important components of road construction that always needs special attention during the whole period of design, execution and operation. To ensure that the stairs are regularly inspected, evaluated and operated, management is needed to meet this need in the stairs by performing appropriate maintenance and repairs. Therefore, in this study, a three-objective optimization model includes minimization of maintenance costs, maximization of bridge performance index and reliability of bridges. For this purpose, a complex integer mathematical programming model has been developed. In order to solve the problem, a multi-objective particle mass optimization algorithm has been developed. From the solution of the proposed algorithm, different Pareto answers are obtained so that the decision makers can choose the answer from the obtained Pareto answers that is their priority.Also, after performing a sensitivity analysis on the parameters of failure rate and failure rate during the effect, it has been observed that by increasing the scenario number in two cases, which indicates an increase in failure rate and failure rate during the effect, the amount of costs increases and The overall performance of the system has been declining, which seems natural and correct.

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References

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Journal of Structural and Construction Engineering
Volume 8, Issue 11 - Serial Number 51
February 2022
Pages 115-141

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History

  • Receive Date: 13 December 2020
  • Revise Date: 24 April 2021
  • Accept Date: 13 May 2021

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