Robust Models for Location and Inventory Decisions in Emergency-grain Depots

DOI

10.2991/msmi-16.2016.45How to use a DOI?

Keywords

location-inventory; uncertainty; robust optimization; emergency grain depots

Abstract

The paper presents two robust models to solve the location-inventory problem occurring in the emergency grain depots (EGD) when demands are uncertain. The proposed model simultaneously determines the location of EGDs, the grain inventory at each employed EGD and the allocation of grain among emergency sites, with the objective of minimizing the system-wide cost which includes EGDs construction cost, grain inventory cost and grain transportation cost. Firstly, a mixed integer programming model is built for the deterministic problem. Secondly, two robust optimization models are established for the case when the demand volume of grain in each emergency site is uncertain. The two robust models, respectively, correspond to the Soyster [1] robust optimization model which is dedicated to the worst case, and the budget optimization model which was proposed by Brtsimas & Sim [2] and has the advantage to control the robust level. Extensive numerical experiments are conducted to show the benefits of the two proposed robust optimization models. Interesting insights related to the problem are presented as well.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yu Fan
AU  - Can-Rong Zhang
PY  - 2016/08
DA  - 2016/08
TI  - Robust Models for Location and Inventory Decisions in Emergency-grain Depots
BT  - Proceedings of the 2016 International Conference on Management Science and Management Innovation
PB  - Atlantis Press
SP  - 187
EP  - 190
SN  - 2352-5428
UR  - https://doi.org/10.2991/msmi-16.2016.45
DO  - 10.2991/msmi-16.2016.45
ID  - Fan2016/08
ER  -