MILP-based model for approximating non-stationary (R, S) policies with correlated demands

Mengyuan Xiang, Roberto Rossi, Belen Martin-Barragan, S. Armagan Tarim

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper addresses the single-item single-stock location stochastic lotsizing
problem under (R, S) policy. We assume demands in different periods
are dependent. We present a mixed integer linear programming (MILP) model
for computing optimal (R, S) policy parameters, which is built upon the conditional
distribution. Our model can be extended to cover time-series-based
demand processes as well. Our computational experiments demonstrate the
effectiveness and versatility of this model.
Original languageEnglish
Pages17-22
Number of pages6
Publication statusPublished - Aug 2017
Eventthe 8th International Workshop on Lot Sizing - Glasgow, United Kingdom
Duration: 23 Aug 201725 Aug 2017

Workshop

Workshopthe 8th International Workshop on Lot Sizing
Abbreviated titleIWLS 2017
CountryUnited Kingdom
CityGlasgow
Period23/08/1725/08/17

Fingerprint Dive into the research topics of 'MILP-based model for approximating non-stationary (R, S) policies with correlated demands'. Together they form a unique fingerprint.

Cite this