Production planning using a hybrid simulation – analytical approach

Byrne, Mike; Bakır, M. Akif

doi:10.1016/s0925-5273(98)00104-2

Cited by 143 publications

(75 citation statements)

References 4 publications

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“…Their simple form permits direct inclusion in the LP model. In iterative approaches (Hung and Leachman 1996;Byrne and Bakir 1999;Hung and Hou 2001;Kim and Kim 2001;Riano 2002), the LP model is solved several times where each time the variables that specify the PU behavior are updated. These updated values are obtained from a separate, descriptive PU model.…”

Section: Literaturementioning

confidence: 99%

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Lead time anticipation in Supply Chain Operations Planning

2011

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Linear programming (LP) models for Supply Chain Operations Planning are widely used in Advanced Planning Systems. The solution to the LP model is a proposal for order releases to the various production units (PU) in the supply network. There is a non-linear relationship between the work-in-process in the PU and the lead time that is difficult to capture in the LP model formulation. We propose a two-step lead time anticipation (LTA) procedure where the LP model is first solved irrespective of the available production capacity and is subsequently updated with aggregate order release targets. The order release targets are generated by a local smoothing algorithm that accounts for the evolution of the stochastic workload in the PU. A solution that is both feasible with respect to the planned lead time and meets the material requirements may not exist. By means of discrete event simulation, we compare a conservative strategy where the production quantities are reduced to an optimistic strategy where the planned lead time constraint is allowed to be violated.

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Section: Literaturementioning

confidence: 99%

“…These updated values are obtained from a separate, descriptive PU model. In Hung and Leachman (1996), Byrne and Bakir (1999) and Kim and Kim (2001), this model is a simulation model and in Hung and Hou (2001) and Riano (2002) this model is the M/M/1 queueing model.…”

Section: Literaturementioning

confidence: 99%

Lead time anticipation in Supply Chain Operations Planning

2011

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“…This iteration is repeated until convergence. Other models based on the idea of iterating between optimisation and simulation models have been proposed by Byrne and Bakir (1999), Byrne and Hossain (2005), Riaño (2003) and Kim and Kim (2001). However, the convergence of these methods is not well understood and may depend on the structure of the underlying production system (Irdem et al, 2010).…”

Section: Approaches Assuming Deterministic Demandmentioning

confidence: 99%

Production planning with load-dependent lead times and safety stocks for a single product

Ravindran

Kempf

Uzsoy

2011

IJPS

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Queuing models have demonstrated the nonlinear relationship between resource utilisation, which is determined by production planning decisions, and lead times. Both production planning decisions and safety stock levels are driven by lead times, and are thus tightly interrelated. However, production planning and safety stock calculations have generally been carried out separately. We propose a production planning model for a single-stage single-product system that integrates release planning and safety stock considerations. Concave clearing functions are used to capture the nonlinear relationship between resource utilisation and lead times, while chance constraints represent the need to plan inventories to achieve desired service levels. Extensive computational experiments indicate that the proposed model provides an excellent tradeoff between customer service and inventory costs.

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“…Yong Hae Lee and Sool Han Kim [21] propose a hybrid approach combining the analytic and simulation model for production-distribution planning in supply chain, considering capacity constraints. Byrne and Bakir [22] study a hybrid algorithm combining mathematical programming and simulation models of manufacturing system for the multi-period and multi-product production planning problem. They suggest the usefulness of a hybrid method showing the solution from the analytic model cannot de acceptable in real world.…”

Section: Hybrid Modelsmentioning

confidence: 99%

“…They suggest the usefulness of a hybrid method showing the solution from the analytic model cannot de acceptable in real world. Kim and Kim [23] extend the idea of Byrne and Bakir [22] to find the capacityfeasible production plan using the analytic and the simulation model. They propose a methodology to properly modify both the left-hand and the right-hand sides of the capacity constraints in the analytic model, using the results of the simulation model.…”

Section: Hybrid Modelsmentioning

confidence: 99%