Vehicle technologies and bus fleet replacement optimization: problem properties and sensitivity analysis utilizing real-world data

This research presents a bus fleet replacement optimization model to analyze vehicle replacement decisions when there are competing technologies. The focus of the paper is on sensitivity analysis. Model properties that are useful for sensitivity analysis are derived and applied utilizing real-world data from King County (Seattle) transit agency. Two distinct technologies, diesel hybrid and conventional diesel vehicles, are studied. Key variables affecting optimal bus type and replacement age are analyzed. Breakeven values and elasticity values are estimated. Results indicate that a government purchase cost subsidy has the highest impact on optimal replacement periods and total net cost. Maintenance costs affect the optimal replacement age but are unlikely to change the optimal vehicle type. Greenhouse gas emissions costs are not significant and affect neither bus type nor replacement age.

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