Distributionally robust inventory routing problem to maximize the service level under limited budget
Feifeng Zheng and
Transportation Research Part E: Logistics and Transportation Review, 2019, vol. 126, issue C, 190-211
This paper studies a stochastic inventory routing problem with alternative handling modules and limited capital budget, under partial distributional information (i.e., the mean and covariance matrix of customer demands). The objective is to maximize the service level, i.e., the probability of jointly ensuring no stockout and respecting the warehouse capacities for all customers at the end of each period. A novel distributionally robust chance constrained formulation is proposed. The sample average approximation method and a model-based hierarchical approach based on problem analysis are developed. Computational results show that the latter approach is more efficient. We also draw some managerial insights.
Keywords: Inventory routing problem; Stochastic optimization; Distributionally robust; Ambiguity set; Service level (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:transe:v:126:y:2019:i:c:p:190-211
Ordering information: This journal article can be ordered from
http://www.elsevier. ... 600244/bibliographic
Access Statistics for this article
Transportation Research Part E: Logistics and Transportation Review is currently edited by W. Talley
More articles in Transportation Research Part E: Logistics and Transportation Review from Elsevier
Bibliographic data for series maintained by Haili He ().