A Generalized Benders Decomposition based algorithm for an inventory location problem with stochastic inventory capacity constraints

Tapia-Ubeda, Francisco J.; Miranda, Pablo A.; Macchi, Marco

doi:10.1016/j.ejor.2017.12.017

Cited by 23 publications

(10 citation statements)

References 50 publications

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“…First, as this paper aims to contribute to the literature on the ILIP in the context of designing the low-carbon SCN with sustainable operations, we classify in Table 1.1 the published ILIP papers related to some critical features, such as the consideration of stochasticity, model formulation, inventory policy, and solution approach. A few recent studies proposed joint location-inventory models dealing with uncertain demand and revealed that optimizing both strategic location-allocation decisions and tactical inventory control decisions simultaneously can reduce the supply chain overall cost, and lead to optimal solutions (Puga & Tancrez, 2017;Shahabi et al, 2018;Tapia-Ubeda et al, 2018;Amiri-Aref et al, 2018). However, none of these works investigated the optimal location-inventory decisions with consideration of the low-carbon sustainability and the emission-compliance of the SCN.…”

Section: Literature Reviewmentioning

confidence: 99%

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Wang

Kafa

et al. 2020

Transportation Research Part E: Logistics and Transportation Re

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Section: Literature Reviewmentioning

confidence: 99%

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Wang

Kafa

et al. 2020

Transportation Research Part E: Logistics and Transportation Re

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“…Therefore, the set of optimality cuts at iteration k can be written as shown in ( 11). It is worth to be mentioned that the proposed solution approach does not incorporates feasibility cuts by ensuring the feasibility of the SbP at each iteration by adding valid inequalities into the MP (see Tapia-Ubeda et al, 2018b). Notice that ,, DV  denotate fixed and known values for the SbP variables.…”

Section: Generalized Benders Decomposition-based Solution Approachmentioning

confidence: 99%

“…(s, Q), and then is not straight applicable to the general model introduced in this paper and in Tapia- Ubeda et al (2018a) . Thus, the proposed solution approach represents a generalization of the algorithm in Tapia- Ubeda et al (2018b), denoting a relevant contribution of this paper.…”

Section: Introductionmentioning

confidence: 99%

Modelling and solving spare parts supply chain network design problems

Tapia-Ubeda

Miranda

Roda

et al. 2020

International Journal of Production Research

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Spare parts are key operational assets in order to minimize the unexpected equipment downtimes that may significantly impact the company results.Accordingly, the spare parts supply chain network supports the entire spare parts operations and it is essential to achieve the planned goals. However, traditional literature on spare parts management has not focused on the underlying supply chain network. Thus, this paper studies the integration of supply chain network design and control with traditional spare parts management. In particular, this paper proposes a generic network optimization modelling structure, with simultaneous decisions for warehouse locations and inventory control, allowing to optimize the total costs of the spare parts supply chain network. The generic model is specified based on three inventory control policies widely used in industrial sites, i.e. (s, Q), (R, s, S) and (S-1, S), which are suitable for managing a great variety of spare parts. Furthermore, a decomposition-based solution approach is also proposed based on generalized Benders decomposition. Finally, numerical results obtained from a real-world case of application on the process industry are shown and discussed.

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“…Tapia-Ubeda et al [40] studied an ILP for a supply chain consisting of two levels, with warehouses shipping product to customers. They developed a mixed integer nonlinear programming model to be solved using a Benders Decomposition algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands

et al. 2018

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Industrial systems, such as logistics and supply chain networks, are complex systems because they comprise a big number of interconnected actors and significant nonlinear and stochastic features. This paper analyzes a distribution network design problem for a four-echelon supply chain. The problem is represented as an inventory-location model with uncertain demand and a continuous review inventory policy. The decision variables include location at the intermediate levels and product flows between echelons. The related safety and cyclic inventory levels can be computed from these decision variables. The problem is formulated as a mixed integer nonlinear programming model to find the optimal design of the distribution network. A linearization of the nonlinear model based on a piecewise linear approximation is proposed. The objective function and nonlinear constraints are reformulated as linear formulations, transforming the original nonlinear problem into a mixed integer linear programming model. The proposed approach was tested in 50 instances to compare the nonlinear and linear formulations. The results prove that the proposed linearization outperforms the nonlinear formulation achieving convergence to a better local optimum with shorter computational time. This method provides flexibility to the decision-maker allowing the analysis of scenarios in a shorter time.

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A Generalized Benders Decomposition based algorithm for an inventory location problem with stochastic inventory capacity constraints

Abstract: Ubeda (a)(b) , Pablo A. Miranda (a)(c) , Marco Macchi (b)

Cited by 23 publications

References 50 publications

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Carbon emission-compliance green location-inventory problem with demand and carbon price uncertainties

Modelling and solving spare parts supply chain network design problems

Design of a Logistics Nonlinear System for a Complex, Multiechelon, Supply Chain Network with Uncertain Demands

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