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Analyzing the Impact of Depreciation-Estimating Methods on State Transportation Agencies’ Equipment Replacement Decisions Using Dynamic Programming by Lei Qiao; Yongwei Shan; Saurav Shrestha; Samir Ahmed; Tieming Liu is a Decision Sciences article available to read on EtoBox.

What is Analyzing the Impact of Depreciation-Estimating Methods on State Transportation Agencies’ Equipment Replacement Decisions Using Dynamic Programming about?

Replacing equipment at the most economical time not only helps to save state transportation agencies (STAs) costs for operating the fleet but also keeps the fleet's level of service at an optimal level. Prior research studies focused on developing alternative economicoriented equipment replacement models rather than the equivalent annual cost (EAC) model to achieve better economic decisions. In addition, various optimization techniques were applied to equipment replacement problems with different objectives, constraints, and contexts. However, few studies examined the impact of depreciation estimation on the equipment replacement decision within STAs by minimizing total equipment cost over a finite study period using the dynamic programming optimization method. This study performed a case study of two class codes of equipment [1.5 m 3 (2-yd) diesel engine front-end loaders and 0.453 t (half-ton) fleetside pickup trucks] to analyze the impact of different depreciation calculations on equipment replacement decisions. Using real-world data provided by the Oklahoma Department of Transportation, the study showed that the double-declining balance depreciation method substantially reduces

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Author

Lei Qiao; Yongwei Shan; Saurav Shrestha; Samir Ahmed; Tieming Liu

Publisher

American Society of Civil Engineers (ASCE)

Published

2023

Language

EN

Field

Decision Sciences (Social Sciences)