Stochastic Benders decomposition for the supply chain investment planning problem under demand uncertainty

Oliveira, Fabrício; Hamacher, Śılvio

doi:10.1590/s0101-74382012005000027

Cited by 9 publications

(3 citation statements)

References 21 publications

(9 reference statements)

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“…Exploiting the structure of the two-stage stochastic programming models, Birge & Louveaux (1997) extended the method to a version considering multiple cuts (multi-cut L-Shaped). The computational efficiency of Benders decomposition has been widely confirmed by different studies in the literature, especially in the context of two-stage stochastic programming, as demonstrated by Costa (2005), Khodr et al (2009), Oliveira & Hamacher (2012), and Bertsimas et al (2013), for instance. However, in some cases, the classical Benders decomposition (or L-Shaped method) may not present satisfactory computational efficiency.…”

Section: Introductionmentioning

confidence: 79%

An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming

Santos

Oliveira

2019

European Journal of Operational Research

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This paper presents the development of an enhanced L-Shaped method applied to an inventory management problem that considers a replenishment control system based on the periodic review ( , ) policy. We consider single-item one-echelon problems with uncertain demands and partial backorder that are modeled using two-stage stochastic programming. To enable the consideration of large-scale problems, the classical single-cut L-Shaped method and its extended multi-cut form were initially applied. Preliminary computational results indicated that the classical L-Shaped method outperformed its multi-cut counterpart, even though the former required more iterations to converge to the optimal solution. This observation inspired the development of the techniques presented for enhancing the L-Shape method, which consist of the combination of a novel acceleration technique with an efficient formulation and valid inequalities for the proposed model. Numerical experiments suggest that the proposed approach significantly reduced the computational time required to solve large-scale problems.

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Section: Introductionmentioning

confidence: 79%

An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming

Santos

Oliveira

2019

European Journal of Operational Research

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“…The most important studies in the petroleum supply chain field such as different linear planning models (Fernandes et al, 2013;Gao, 2018) random linear planning models in petroleum product supply chain strategic, operational and tactical planning (Al-Othman et al, 2008;MirHassani, 2008;Ribas et al, 2010;MirHassani and Noori, 2011;Tong et al, 2012;Leiras et al, 2013;Oliveira et al, 2013;Oliveira and Hamacher, 2012a;Fernandes et al, 2017;Lima et al, 2017Lima et al, , 2018aOliveira et al, 2014) linear/non-linear complex integer planning (Guajardo et al, 2013;Kuo and Chang, 2008;Pinto et al, 2000;Neiro and Pinto, 2004), fuzzy linear planning (Ghatee and Hashemi, 2009), robust planning (Lima et al, 2018b(Lima et al, , 2019, twolevel planning (Gao and You, 2019;Zang et al, 2020;Oliveira and Hamacher, 2012b) and multi-objective planning (Gholami et al, 2019). As visible, these planning models lack multiobjective functions.…”

Section: Literature Reviewmentioning

confidence: 99%

A mathematical tri-level programming model for designing an integrated dynamic petroleum product supply chain

Ahwazian

Amindoust

Tavakkoli–Moghaddam

et al. 2022

JAMR

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PurposeThe purpose of this paper is to design petroleum products’ supply chain management, which includes efficient integration of suppliers, manufacturers, storehouses and retailers.Design/methodology/approachThis paper proposes that a three-level supply chain will be turned into a bi-level supply chain of petroleum products by simultaneous integration of the middle level with the upstream and downstream levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels. Also, it is integrally optimized by considering the multiple managerial flows' mutual results at various supply chain levels.FindingsThe concepts of the design, structure and outputs are led by the model's solution. The model also responds to the variations in the market via coordination in the related decisions to the distribution, production and inventory issues, and also coordinating between the demands and production.Research limitations/implicationsThis paper has limited its analysis to definite values due to the over-expansion of calculations and analysis. Future works can study other aspects of the proposed model for a multi-level petroleum product supply chain in different states of certain parameters and time zones.Practical implicationsThe designed model can directly and transparently help the oil managers and decision-makers lower the costs of manufacturing, distribution and sales with respect to the determined criteria.Originality/valueThis paper establishes that effectiveness of the dynamic petroleum materials supply chain design will increase by considering maintained and increased production costs and coordinate management flows at all levels by supply chain creation’s integration.

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“…There are other important studies in this regard. ,− The third group has focused only on crude oil transportation. The most important papers in this group are refs − .…”

Section: Introductionmentioning

confidence: 99%

Optimum Integrated Design of Crude Oil Supply Chain by a Unique Mixed Integer Nonlinear Programming Model

Azadeh

Shafiee

Yazdanparast

et al. 2017

Ind. Eng. Chem. Res.

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In this paper, a mixed integer nonlinear programming model is proposed to concurrently design two segments (i.e., upstream and midstream) of crude1 oil supply chain. The network includes all entities and their connections from oil wells to product depots. Furthermore, a real world example is applied to show the improved model application. Furthermore, a sensitivity analysis in which ±20% deviations at a time were placed on two parameters is presented. Also, model performance is analyzed with GAMS 22.6. The proposed multiperiod and multiproduct model consists of several decisions (i.e., oil field development, transformation, transportation, and distribution). The main contributions of this work are inclusion of all entities related to upstream and midstream segments and both oil field development and transformation planning, simultaneously. Finally, it is shown that a decrease in production cost of refinery products will lead to more net profit given all refinery production capacity are used. Also, increase in refinery production capacity will improve network net profit given new fixed cost investment is not applied (e.g., refineries and transportation modes). This is the first study that simultaneously considers and optimizes upstream and midstream of crude oil supply chain. Second, it presents a unique mathematical model. Third, all features and parameters are included. Fourth, it is practical and may be used for other crude oil supply chain.

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Stochastic Benders decomposition for the supply chain investment planning problem under demand uncertainty

Cited by 9 publications

References 21 publications

An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming

An enhanced L-Shaped method for optimizing periodic-review inventory control problems modeled via two-stage stochastic programming

A mathematical tri-level programming model for designing an integrated dynamic petroleum product supply chain

Optimum Integrated Design of Crude Oil Supply Chain by a Unique Mixed Integer Nonlinear Programming Model

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