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Sila Cetinkaya

Publications and source records attributed to Sila Cetinkaya.

3 recordsLinked to original sources

Inbound Replenishment and Outbound Dispatch Decisions under Hybrid Shipment Consolidation Policies: An Analytical Model and Comparison

We consider a distribution warehouse where both the inbound inventory replenishment and outbound dispatch decisions are subject to fixed (as well as per-unit) transportation charges and demand is stochastic. In order to realize scale economies associated with transportation operations both on the outbound and inbound sides, dispatch schedules must be synchronized over time with inventory replenishment decisions. An immediate delivery policy on the outbound side does not make economic sense because outbound dispatch operations and costs will benefit from a temporal shipment consolidation policy. Our particular interest in this setting is the exact modeling and analysis of hybrid shipment consolidation policies, in comparison to the time- and quantity-based counterparts. Since shipment consolidation prolongs customer waiting and inventory holding, we investigate average delay penalty per order and average inventory per time unit as critical measures of performance of the distribution operation, along with the annual cost. By fixing the expected inbound replenishment and outbound dispatch frequencies, we compare these measures among the alternative ways of operation under hybrid, time-based, and quantity-based policies. This comparison then lends itself to an explicit analytical comparison of average costs under these three policies, without a need for solving the corresponding optimization problems.

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Analytical Results on the Service Performance of Stochastic Clearing Systems

Stochastic clearing theory has wide spread applications in the context of supply chain and service operations management. Historical application domains include bulk service queues, inventory control, and transportation planning (e.g., vehicle dispatching and shipment consolidation). In this paper, motivated by a fundamental application in shipment consolidation, we revisit the notion of service performance for stochastic clearing system operation. More specifically, our goal is to evaluate and compare service performance of alternative operational policies for clearing decisions, as quantified by a measure of timely service referred as \emph{Average Order Delay} ($AOD$). All stochastic clearing systems are subject to service delay due to the inherent clearing practice, and $AOD$ can be thought of as a benchmark for evaluating timely service. Although stochastic clearing theory has a long history, existing literature on the analysis of $AOD$ as a service measure has several limitations. Hence, we extend the previous analysis by proposing a more general method for a generic analytical derivation of $AOD$ for any renewal-type clearing policy, including but not limited to alternative shipment consolidation policies in the previous literature. Our proposed method utilizes a new martingale point of view and lends itself for a generic analytical characterization of $AOD$, leading to a complete comparative analysis of alternative renewal-type clearing policies. Hence, we also close the gaps in literature on shipment consolidation via a complete set of analytically provable results regarding $AOD$ which were only illustrated through numerical tests previously.

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Stochastic Clearing Systems with Multiple Input Processes

In this paper, we consider stochastic clearing systems with multiple drifted Brownian motion inputs. First, we propose an instantaneous rate policy, which is shown to be the optimal one among a large class of renewal type clearing policies in terms of average cost. Second, we propose a service measure about average weighted delay rate, and provide a unified method to calculate the service measure under different clearing policies. Moreover, we prove that under a fixed clearing frequency, the instantaneous rate policy outperforms a large class of clearing policies, and the instantaneous rate hybrid policy performs better than time-based policy, in terms of average weighted delay rate.

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