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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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Quartile: search.filters.quartile.Q4Subject: search.filters.subject.Operations research and management science

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Now showing 1 - 3 of 3
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    PublicationOpen Access
    The state-dependent M/G/1 queue with orbit
    (Springer, 2018) Baron, Opher; Economou, Antonis; Department of Industrial Engineering; Manou, Athanasia; Faculty Member; Department of Industrial Engineering; College of Engineering
    We consider a state-dependent single-server queue with orbit. This is a versatile model for the study of service systems, where the server needs a non-negligible time to retrieve waiting customers every time he completes a service. This situation arises typically when the customers are not physically present at a system, but they have a remote access to it, as in a call center station, a communication node, etc. We introduce a probabilistic approach for the performance evaluation of this queueing system, that we refer to as the queueing and Markov chain decomposition approach. Moreover, we discuss the applicability of this approach for the performance evaluation of other non-Markovian service systems with state dependencies.
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    PublicationOpen Access
    Recent advances in computational biology, bioinformatics, medicine, and healthcare by modern OR
    (Springer, 2014) Weber, Gerhard-Wilhelm; Blazewicz, Jacek; Rauner, Marion; Department of Industrial Engineering; Türkay, Metin; Faculty Member; Department of Industrial Engineering; College of Engineering; 24956
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    PublicationOpen Access
    Pricing and lot-sizing decisions for perishable products when demand changes by freshness
    (American Institute of Mathematical Sciences, 2021) Kaya, Onur; Department of Industrial Engineering; Bayer, Halit; Department of Industrial Engineering; Graduate School of Sciences and Engineering
    Perishable products like dairy products, vegetables, fruits, pharmaceuticals, etc. lose their freshness over time and become completely obsolete after a certain period. Customers generally prefer the fresh products over aged ones, leading the perishable products to have a decreasing demand function with respect to their age. We analyze the inventory management and pricing demand function. A stochastic dynamic programming model is developed in when and how much inventory to order and how to price these products considering their freshness over time. We prove the characteristics of the optimal solution of the developed model and extract managerial insights regarding the optimal inventory and pricing strategies. The numerical studies show that dynamic pricing can lead to signiffcant savings over static pricing under certain parameter settings. In addition, longer replenishment cycles are seen under dynamic pricing compared to static pricing, even though similar uantities are ordered in each replenishment.