Integrated Supply Chain Management via Randomized Rounding

Lehilton L. C. Pedrosa () and Maxim Sviridenko ()
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Lehilton L. C. Pedrosa: Institute of Computing, University of Campinas, Campinas-SP, 13083-852, Brazil
Maxim Sviridenko: Yahoo! Labs, New York, New York 10022

INFORMS Journal on Computing, 2018, vol. 30, issue 1, 124-136

Abstract: We consider the supply chain problem of minimizing ordering, distribution, and inventory holding costs of a supply chain formed by a set of warehouses and retailers over a finite time horizon, which we call the production and distribution problem . This is a common generalization of the classical metric facility location problem and joint replenishment problem that coordinates the network design and inventory management decisions in an integrated manner. This coordination can represent significant economy for many applications, where network design and operational costs are normally considered separately. This problem is considered when the instances satisfy assumptions such as metric space of warehouse and retailer locations, and monotonic increasing inventory holding costs. In this work, we give a 2.77-approximation based on the randomized rounding of the natural mixed-integer programming relaxation. Also, we give a 5-approximation for the case that objective function includes retailer ordering setup costs.

Keywords: approximation algorithms; integrated inventory management; facility location; LP-rounding (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:30:y:2018:i:1:p:124-136

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