Improving the push-pull strategy in a serial supply chain by a hybrid push-pull control with multiple pulling points

Seung Hwan Kim, John Fowler, Dan Shunk, Michele E. Pfund

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Because of its benefits - from lowered inventory costs to greater flexibility in adapting to shifting market forces - the push-pull strategy is being widely used in today's competitive supply-chain designs. The push-pull strategy also brings potential supply-chain risks related to order fulfilment capability and robustness against external variability. More specifically, the use of this strategy often results in an inability to minimise the impact of lead-time variability. We present a new, hybrid push-pull strategy that incorporates additional stock points after the push-pull boundary as the pulling points in a serial supply chain, which can mitigate the risks and improve the robustness of the push-pull strategy without sacrificing its benefits in inventory cost reduction. For the evaluation and comparison of different supply-chain strategies, a nonlinear, mixed-integer programming model with a cost-minimisation objective function is developed and implemented in the numerical experimentation, with simulated annealing as the search algorithm. Results from the experiments demonstrate the potential improvement by our proposed strategy in terms of the robustness and cost-effectiveness against external variability. The results also verify the risks and limitations of the conventional push-pull strategy and provide some managerial implications regarding the use of push-pull supply chains.

Original languageEnglish (US)
Pages (from-to)5651-5668
Number of pages18
JournalInternational Journal of Production Research
Volume50
Issue number19
DOIs
StatePublished - Oct 1 2012

Keywords

  • Metaheuristics
  • Optimisation
  • Push/pull systems
  • Supply-chain management

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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