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dc.contributor.authorBhunia, A.K.-
dc.contributor.authorShaikh, Ali Akbar-
dc.contributor.authorMaiti, A.K.-
dc.contributor.authorMaiti, M.-
dc.date.accessioned2022-04-26T09:04:44Z-
dc.date.available2022-04-26T09:04:44Z-
dc.date.issued2013-
dc.identifier.issn1923-2934-
dc.identifier.issn1923-2926-
dc.identifier.urihttp://111.93.204.14:8080/xmlui/handle/123456789/576-
dc.description.abstractThis paper deals with a deterministic inventory model developed for deteriorating items having two separate storage facilities (owned and rented warehouses) due to limited capacity of the existing storage (owned warehouse) with linear time dependent demand (increasing) over a fixed finite time horizon. The model is formulated with infinite replenishment and the successive replenishment cycle lengths are in arithmetic progression. Partially backlogged shortages are allowed. The stocks of rented warehouse (RW) are transported to the owned warehouse (OW) in continuous release pattern. For this purpose, the model is formulated as a constrained non-linear mixed integer programming problem. For solving the problem, an advanced genetic algorithm (GA) has been developed. This advanced GA is based on ranking selection, elitism, whole arithmetic crossover and non-uniform mutation dependent on the age of the population. Our objective is to determine the optimal replenishment number, lot-size of two-warehouses (OW and RW) by maximizing the profit function. The model is illustrated with four numerical examples and sensitivity analyses of the optimal solution are performed with respect to different parameters.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Industrial Engineering Computations (Growing Science Ltd.)en_US
dc.subjectInventory managementen_US
dc.subjectTwo-storageen_US
dc.subjectDeteriorationen_US
dc.subjectGenetic algorithmen_US
dc.subjectPartial backloggingen_US
dc.subjectFinite time horizonen_US
dc.titleA two warehouse deterministic inventory model for deteriorating items with a linear trend in time dependent demand over finite time horizon by Elitist Real-Coded Genetic Algorithmen_US
dc.typeArticleen_US
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