Simple heuristic for the strategic supply chain design of large-scale networks: A Brazilian case study

Farias, Everton da Silveira; Li, Jingquan; Galvez, J.; Borenstein, Denis

doi:10.1016/j.cie.2017.07.017

Cited by 7 publications

(6 citation statements)

References 37 publications

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“…We use the arc-flow MILP model from Farias et al (2017), which is presented here for the sake of completeness. Constraints are imposed on the raw materials supply, production capacity, DC capacity, and demand of CZs.…”

Section: Formulationmentioning

confidence: 99%

“…However, due to the complexity of the problem, the previously mentioned solution methods were only able to solve instances with very limited number of elements in the network, using artifices such as product aggregation to solve real-world problems. Farias et al (2017) pointed out this issue and developed a multi-start based heuristic to solve large instances of the problem. Although the results were quite impressive in terms of the dimensions of the solved instances, the developed method requires intensive experiments to set up important parameters to obtain good solutions for each different configurations of the problem instances, in terms of the number of products, CZs, and DCs.…”

Section: Introductionmentioning

confidence: 99%

“…The solution approach is an extension of the heuristic introduced in Farias et al (2017), by integrating a local search in the solution process, we present a two-stage heuristic framework for efficiently solving the deterministic, four-echelon, multi-product, single-source strategic SCND problem for very large-scale problems. The first stage is a constructive phase in which a multistart layered-based rounding algorithm proposal in Farias et al (2017) to find several possible feasible solutions. The second phase is based on a local search heuristic to improve the solutions delivered by the previous phase.…”

Section: Introductionmentioning

confidence: 99%

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mentioning

confidence: 99%

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Large Scale Supply Chain Network Design: An Effective Heuristic Approach

Galvez

Guedes

2023

Pesqui. Oper.

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This work considers the strategic Supply Chain Network Design (SCND) problem, which is to define the number and location of facilities, and the flow of products among them to fulfilling a long-term deterministic demand. A two-phase heuristic approach was specially developed to solve large scale problems in reasonable time, extending a previous algorithm introduced in Farias et al. (2017). In the construction phase, a multi-start approach was developed to generate diversified initial solutions from each new iteration of a layered-based rounding heuristic. In the second phase, a local search heuristic improves the solution provided by the rounding method. The solution method is evaluated using randomly generated instances, and a evaluated strategic of marketing in a real case study applied to a company to redesigning the supply chain to two lines of products.The obtained results evidence the effectiveness and flexibility of the developed approach for handling very large instances.

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Section: Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…

…”

mentioning

confidence: 99%

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Large Scale Supply Chain Network Design: An Effective Heuristic Approach

Galvez

Guedes

2023

Pesqui. Oper.

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“…Network optimization models frequently exclude inventory decisions and costs [1]. Several works that deal with network design do not consider inventory holding costs for decision making [2,3].…”

Section: Introductionmentioning

confidence: 99%

The impact of inventory holding costs on the strategic design of supply chains

Bolaños-Zúñiga

Holguín

2020

Rev.Fac.Ing.Univ.Antioquia

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The explicit consideration of inventory holding costs for the strategic design of supply chains has not been sufficiently addressed in scientific literature. A possible cause is that usually supply chain optimization models are deterministic and linear or mixed-integer linear, while forecasting methods and inventory control systems are stochastic and non-linear. It is clear, however, that inventory costs might have a significant impact on optimal supply chain configuration and on distribution systems expansion or contraction. This article presents a practical strategy that considers an item-by-item inventory control system by means of a Monte Carlo simulation model as a starting point to include inventory holding costs in a supply chain optimization model. Three strategies to include inventory costs in the objective function were analyzed: The Square Root Law (SRL), the potential functions that relate average inventory with warehouse throughput, and the estimation of average inventories by simulation. The results suggest that the SRL should not be used unless unusual assumptions hold and that potential functions are a very good approximation to consider inventory costs for supply chain configuration.

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