Document Type: Original Article

Authors

School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

Abstract

This paper addresses an integrated multi-echelon location-allocation-inventory problem in a ‎stochastic ‎supply chain. In a bid to be more realistic, the demand and lead time are considered ‎to be hemmed in by ‎uncertainty. To tackle the proposed supply chain network design problem, ‎a two-phase approach based ‎on queuing and optimization models is devised. The queuing ‎approach is first deployed, which is able to ‎cope with inherent uncertainty of parameters. ‎Afterwards, the proposed supply chain network design ‎problem is formulated using a mixed‏-‏integer nonlinear model. Likewise, the convexity of the model is ‎proved and the optimal ‎inventory policy as closed-form is acquired. Inasmuch as the concerned problem ‎belongs to ‎NP-hard problems, two meta-heuristic algorithms are employed, which are capable ‎of ‎circumventing the complexity burden of the model. The numerical examples evince the efficient ‎and ‎effective performance of the solving algorithms. Lastly, sensitivity analyses are conducted ‎through ‎which interesting insights are gained.‎

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