Conditional Leadtime Flexibility in an Assemble-to-Order System

31 Pages Posted: 9 Sep 2022

See all articles by Tianhu Deng

Tianhu Deng

Tsinghua University

Jing-Sheng Jeannette Song

Duke University - Fuqua School of Business

Yi Yu

Tsinghua University

Date Written: July 28, 2024

Abstract

Problem definition: We introduce and formalize a concept termed conditional leadtime flexibility (CLF), which refers to the industry practice where a manufacturer requests its upstream suppliers to dynamically adjust the pipeline orders' remaining leadtimes. Over a finite horizon, an assemble-to-order (ATO) manu- facturer makes joint decisions on inventory replenishment and leadtime adjustment to minimize the total discounted expected cost. Methodology/results: The problem is formulated as a multi-period dynamic programming with an enlarged state space to track the adjustable pipeline orders. The replenishment and leadtime adjustment decisions are made sequentially in each period. The analysis reveals that (i) the optimal cost-to-go function is both convex and additively separable; (ii) both the optimal replenishment and lead- time adjustment decisions follow general base-stock policies; and (iii) the convexity and additive separability allow us to perform a derivative analysis on the optimality equations and design an efficient algorithm. Managerial implications: Using real industry data, we numerically find that (i) CLF achieves notable cost savings over a wide range of parameters; (ii) the value of CLF comes from both the order expediting and deferring; and (iii) CLF outperforms dual-sourcing when the unit adjustment cost is less than 40% of the unit ordering cost from the express source. Our findings underscore the importance of CLF. 

Keywords: Conditional leadtime flexibility, assemble-to-order (ATO), inventory planning

JEL Classification: C61

Suggested Citation

Deng, Tianhu and Song, Jing-Sheng Jeannette and Yu, Yi, Conditional Leadtime Flexibility in an Assemble-to-Order System (July 28, 2024). Available at SSRN: https://ssrn.com/abstract=4200574 or http://dx.doi.org/10.2139/ssrn.4200574

Tianhu Deng

Tsinghua University ( email )

Beijing, 100084
China

Jing-Sheng Jeannette Song

Duke University - Fuqua School of Business ( email )

100 Fuqua Drive
Duke University
Durham, NC 27708
United States

HOME PAGE: http://people.duke.edu/~jssong/

Yi Yu (Contact Author)

Tsinghua University ( email )

Beijing, 100084
China

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