A robust optimization model for multi-site production planning problem in an uncertain environment

Leung, Stephen C. H.; Tsang, Sally O. S.; Ng, Wan-Lung; Wu, Yue

doi:10.1016/j.ejor.2006.06.011

Cited by 279 publications

(93 citation statements)

References 18 publications

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“…Since the late 1990s, this approach has been applied broadly in the area of uncertain control and optimization. Several RO approaches are presented in the literature review (e.g., Mulvey et al 1995;Ben-Tal and Nemirovski 1998, 1999Yu and Li 2000), Sim 2003, 2004;Leung et al 2007), (Bozorgi-Amiri et al 2011;Pishvaee et al 2011;Shishebori and Babadi 2015). According to the efficient beneficial properties of the Pishvaee et al (2011) approach for our problem, in this study, this robust approach is considered which is conducive to cope with the related parameter uncertainty.…”

Section: Solution Approach a Hintmentioning

confidence: 99%

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Shishebori

Babadi

2017

J Ind Eng Int

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This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

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Section: Solution Approach a Hintmentioning

confidence: 99%

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Shishebori

Babadi

2017

J Ind Eng Int

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“…According to the easy understanding of the Mulvey approach for many designers/architects and the scenario-based approach of the problem, this robust approach is considered which is conducive to cope of the related parameter uncertainty. For more detail reading about this robust optimization approach, we refer readers to Mulvey et al [55], Yu and Li [61], Leung et al, [62] , BozorgiAmiri et al [63], Shishebori and Yousefi-Babadi [37].…”

Section: Robust Optimization Approachmentioning

confidence: 99%

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

2017

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Abstract:This study considers a multi-objective combined budget constrained facility location/network design problem (FL/NDP) in which the system uncertainty is considered. The most obvious practical examples of the problem are territorial designing and locating of academies, airline networks, and medical service centers. In order to assure the network reliability versus uncertainty, an efficient robust optimization approach is applied to model the proposed problem. The formulation is minimizing the total expected costs, including, transshipment costs, facility location (FL) costs, fixed cost of road/link utilization as well as minimizing the total penalties of uncovered demand nodes. Then, in order to consider of several system uncertainty, the proposed model is changed to a fuzzy robust model by suitable approaches. An efficient Sub-gradient based Lagrangian relaxation algorithm is applied. In addition, a practical example is studied. At the following, a series of experiments, including several test problems, is designed and solved to evaluate of the performance of the algorithm. The obtained results emphasize that considering of practical factors (e.g., several uncertainties, system disruptions, and customer satisfaction) in modelling of the problem can lead to significant improvement of the system yield and subsequently more efficient utilization of the established network.

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“…They also present a sampling strategy with an accelerated Benders Decomposition algorithm to quickly compute high quality solutions for large scale supply chain design problems. In addition, a robust optimization model is presented by Leung et al (2007) to address a multi-site production planning problem for a lingerie company. A medium-term planning horizon with an objective of minimizing the total production, inventory, labor, and workforce changing costs are considered.…”

Section: Literature Reviewmentioning

confidence: 99%

Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations

Rastogi

Fowler

Carlyle

et al. 2011

International Journal of Production Economics

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a b s t r a c tA semiconductor supply network involves many expensive steps, which have to be executed to serve global markets. The complexity of global capacity planning combined with the large capital expenditures to increase factory capacity makes it important to incorporate optimization methodologies for cost reduction and long-term planning. The typical view of a semiconductor supply network consists of layers for wafer fab, sort, assembly, test and demand centers. We present a two-stage stochastic integer-programming formulation to model a semiconductor supply network. The model makes strategic capacity decisions, (i.e., build factories or outsource) while accounting for the uncertainties in demand for multiple products. We use the model not only to analyze how variability in demand affects the make/buy decisions but also to investigate how the correlation between demands of different products affects these strategic decisions. Finally, we demonstrate the value of incorporating demand uncertainty into a decision-making scheme.

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A robust optimization model for multi-site production planning problem in an uncertain environment

Cited by 279 publications

References 18 publications

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

Supply network capacity planning for semiconductor manufacturing with uncertain demand and correlation in demand considerations

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