Robust optimization method for multi-stage production and inventory based on shared uncertainty

ZHOU Yi-jia; JIA Ning; XU Li-jun

doi:10.16411/j.cnki.issn1006-7736.2020.04.010

Journal of Dalian Maritime University >

2020 , Vol. 46 >Issue 4: 76 - 84

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2020.04.010

Robust optimization method for multi-stage production and inventory based on shared uncertainty

ZHOU Yi-jia ,
JIA Ning ,
XU Li-jun

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(1. School of Computer and Software, Dalian Neusoft University of Information, Dalian 116023, China; 2. School of Science, Dalian Maritime University, Dalian 116026, China)

Received date: 2020-06-22

Revised date: 2020-10-30

Online published: 2020-10-30

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Abstract

In order to solve the problem of a class of objective and constraints with the same uncertain parameters, taking the multi-stage production and inventory problem as the research object, considering the influence of demand uncertainty on the market, a reasonable adjustable robust model was proposed to maximize profit, and the optimal ratio of output and inventory in supply chain management was obtained. However, the new model was a NPhard problem. Considering the special polyhedral uncertainty set, the robust optimization model sharing uncertain parameters was transformed into an easily solved problem according to duality theory, and its equivalence with the original problem was proved.Through the model analysis, the robust optimization model of shared uncertain parameters is more practical. Numerical experiments show that the model is robust, effective and flexible, and can give a more reasonable production and inventory plan, which has guiding significance for practical problems.

Key words： multi-stage production and inventory; uncertain set; robust optimization; duality theory

Cite this article

ZHOU Yi-jia , JIA Ning , XU Li-jun . Robust optimization method for multi-stage production and inventory based on shared uncertainty[J]. Journal of Dalian Maritime University, 2020 , 46(4) : 76 -84 . DOI: 10.16411/j.cnki.issn1006-7736.2020.04.010

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