Equipment replacement analysis with an uncertain finite horizon

Abstract

Equipment replacement strategies are highly dependent on the horizon of analysis. While the literature can generally be categorized according to infinite or finite-horizon solutions, this paper examines the case where the horizon will last at least T _s periods but may last as long as T _l periods, due to uncertainty in the length of production runs or the temporary provision of services. Stochastic dynamic programming formulations are presented and solutions that minimize either expected costs or maximum regret are explored. Furthermore, the critical time period where optimal decisions diverge for different horizon realizations is identified. As this time period may be substantially earlier than T _s, a lease option contract is designed that allows owners to lower the risk of high costs that may result from a given horizon realization, while opening a possible source of revenue for a leasor.

Keywords:

• Dynamic programming
• life cycle models

Acknowledgements

The authors are grateful to two anonymous referees whose remarks greatly improved this paper. The authors also gratefully acknowledge National Science Foundation support under grant CMMI-0813671.