Large neighbourhood search applied to the efficient solution of spatially explicit strategic supply chain management problems

Copado-Méndez, Pedro J.; Blum, Christian; Guillén‐Gosálbez, Gonzalo; Jiménez, Laureano

doi:10.1016/j.compchemeng.2012.09.006

Cited by 17 publications

(10 citation statements)

References 52 publications

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“…Duan et al [14] presented a new age-based replenishment policy for supply chain inventory optimization of highly perishable products. Copado-Mendez et al [12] applied large neighborhood search to the efficient solution of spatially explicit strategic supply chain management problems. Cardona-Valdes et al [5] presented metaheuristic procedure for a bi-objective supply chain design problem with uncertainty.…”

Section: Supply Chainmentioning

confidence: 99%

A Literature Survey on Metaheuristics in Production Systems

Onar

Öztayşi

Kahraman

et al. 2016

Operations Research/Computer Science Interfaces Series

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Typical problems in production systems are suboptimal production scheduling, long manufacturing lead times, inefficient inventory control, low work center utilization, etc. The solutions of these problems may need complex techniques while the classical techniques are insufficient to solve them. In this chapter we first classified the problems which may be faced in production systems and then the solution techniques called metaheuristics.

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Section: Supply Chainmentioning

confidence: 99%

A Literature Survey on Metaheuristics in Production Systems

Onar

Öztayşi

Kahraman

et al. 2016

Operations Research/Computer Science Interfaces Series

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“…Constraints (5)-(7) model capacity constraints at suppliers, plants and DCs, respectively. In addition, (6) and (7) state that the products can be shipped only to selected facilities.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…To the best of our knowledge, the use of the LNS for solving SCND problems is still very scarce. Copado-Méndez et al [7] model two case studies in chemical engineering and solve them with an LNS approach. The authors identify a benefit of the LNS: removal and repair operators, which are largely dependent on the models to be solved, provide high flexibility.…”

Section: Introductionmentioning

confidence: 99%

A large neighborhood search heuristic for supply chain network design

Eskandarpour

Dejax²,

Péton³

2017

Computers & Operations Research

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International audienceMany exact and approximate solution techniques have been used to solve facility location problems and, more generally, supply chain network design problems. Yet, the Large Neighborhood Search technique (LNS) has almost never been suggested for solving such problems, although it has proven its efficiency and flexibility in solving other complex combinatorial optimization problems. In this paper, we propose an LNS framework for solving a four-layer single period multi-product supply chain network design problem. One important feature of the model is that it includes inter-modality: the itinerary followed by the cargo from origin to destination may take several transportation modes. Moreover, several modes may compete on some arcs. Location decisions for intermediate facilities (e.g. plants and distribution centers) are determined by the LNS while transportation modes and product flow decisions are determined by a greedy heuristic. As a post-optimization step, linear programming is used to optimize product flows once the structure of the logistics network is fixed. Extensive experiments, based on randomly generated instances of different sizes and characteristics, show the effectiveness of the method compared with a state-of-the-art solver

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“…However, for solving supply chain network design (SCND) problems, the use of Large Neighbourhood Search (LNS) has been explored by a few studies (see ref. [32] or [33]), but to the best of our knowledge, LNS (or ALNS) has not been used yet to solve integrated strategic and tactical problems, especially for biomass supply chain design problems.…”

Section: Literature Surveymentioning

confidence: 99%