Process Flexibility: A Distribution-Free Bound on the Performance of K-Chain

45 Pages Posted: 17 Aug 2013 Last revised: 3 Feb 2015

See all articles by Xuan Wang

Xuan Wang

Hong Kong University of Science and Technology, ISOM Department

Jiawei Zhang

New York University (NYU) - Department of Information, Operations, and Management Sciences

Date Written: July 24, 2014

Abstract

Process flexibility has been widely applied in many industries as a competitive strategy to improve responsiveness to demand uncertainty. An important flexibility concept is the long chain proposed by Jordan and Graves. The effectiveness of the long chain has been investigated via numerical as well as theoretical analysis for specific probability distributions of the random demand. In this paper, we obtain in closed-form a distribution-free bound on the ratio of the expected sale of the long chain relative to that of full flexibility. Our bound depends only on the mean and standard deviation of the random demand, but compares very well with the ratio that uses complete information of the demand distribution. This suggests the robustness of the performance of the long chain under different distributions. We also prove a similar result for k-chain, a more general flexibility structure. We further tighten the bounds by incorporating more distributional information of the random demand.

Keywords: Process flexibility, problem of moments, asymptotic analysis, worst-case bound

Suggested Citation

Wang, Xuan and Zhang, Jiawei, Process Flexibility: A Distribution-Free Bound on the Performance of K-Chain (July 24, 2014). Available at SSRN: https://ssrn.com/abstract=2311268 or http://dx.doi.org/10.2139/ssrn.2311268

Xuan Wang (Contact Author)

Hong Kong University of Science and Technology, ISOM Department ( email )

Clear Water Bay
Kowloon
Hong Kong, Not Applicable
Hong Kong
852-23585854 (Phone)

Jiawei Zhang

New York University (NYU) - Department of Information, Operations, and Management Sciences ( email )

44 West Fourth Street
New York, NY 10012
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
729
Abstract Views
3,485
rank
41,302
PlumX Metrics