Ehsan Dehghani; Peyman Taki
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 ...
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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.
Mohammad Ehsanifar; Nima Hamta; Mahshid Hemesy
Abstract
This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing ...
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This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing model. In this regard, to enable decision makers to obtain useful results with enough knowledge on the behavior of system, the queuing system is considered in fuzzy environment in which the arrival and service times are represented by fuzzy variables. The proposed approach for vague systems can represent the system more accurately, and more information is provided for designing queueing systems in real life. Furthermore, simulation method is applied successfully for modeling complex systems and understanding queuing behavior. Finally, a numerical example as a case study in a banking system is solved to show the validity of developed model in the real situation.