Online Demand Fulfillment Under Limited Flexibility
36 Pages Posted: 14 Jul 2018
Date Written: June 23, 2018
Abstract
We study online demand fulfillment in sparse networks with arbitrary numbers of resources and request types, and positive Generalized Capacity Gaps (GCG) introduced by Shi et al.(2016). We show that such a sparse network with limited flexibility is both necessary and sufficient to achieve bounded performance gap compared with networks with full flexibility, extending the work by Asadpour et al. (2016) from the long chains to more general sparse networks. We develop simple inventory allocation rules and guidelines for designing sparse network structures with positive GCGs such as generalized long chains. Numerical experiments and a real case study are conducted to confirm our findings as well as some of the flexibility principals conjectured in the literature.
Keywords: process flexibility, online retailing, dynamic resource allocation
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