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Sharmila Saren

Researcher at Vidyasagar University

Publications -  8
Citations -  503

Sharmila Saren is an academic researcher from Vidyasagar University. The author has contributed to research in topics: Total cost & Economic order quantity. The author has an hindex of 7, co-authored 8 publications receiving 440 citations.

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Product inspection policy for an imperfect production system with inspection errors and warranty cost

TL;DR: A deteriorating production process which randomly shifts to out-of-control state from in- control state is described, which includes a warranty policy for some fixed time periods and is better to use for reducing inspection costs.
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An inventory model with trade-credit policy and variable deterioration for fixed lifetime products

TL;DR: A model to extend Mahata’s 2012 model with time varying deterioration where Mahata wrote exponential deterioration but actually he considered constant deterioration is extended.
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An inventory model with variable demand, component cost and selling price for deteriorating items

TL;DR: In this article, an economic order quantity (EOQ) model for finite production rate and deteriorating items with time dependent increasing demand is developed, where component cost and the selling price are considered at a continuous rate of time.
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Effect of Unequal Lot Sizes, Variable Setup Cost, and Carbon Emission Cost in a Supply Chain Model

TL;DR: In this article, the authors proposed a single-setup multidelivery (SSMD) policy in supply chain management, where the buyer inspects all received products and returns defective items to vendor for reworking process.
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A Stackelberg Game Approach in an Integrated Inventory Model with Carbon-Emission and Setup Cost Reduction

TL;DR: In this paper, an integrated inventory model that allows Stackelberg game policy for optimizing joint total cost of a vendor and buyer system is presented, in which the players of the integrated model are with unequal power (as leader and follower) and the game strategy is utilized to solve this model for obtaining global optimum solution over the finite planning horizon.