BibTex Citation Data :
@article{JM266, author = {Yusti Ernawati and Sunarsih sunarsih}, title = {SISTEM PENGENDALIAN PERSEDIAAN MODEL PROBABILISTIK \"BACK ORDER POLICY\"}, journal = {MATEMATIKA}, volume = {11}, number = {2}, year = {2010}, keywords = {}, abstract = { Inventory represents the amount of reserved raw material to meet demand of consumers in certain period. If the demand is uncertain, the stock cuold be insufficient or becaming excessive. Therefore, it is required to device an optimal inventory rule which concerning all posible factors. In this paper, a probability inventory model with constraint will be applied on a case of back order policy. The constrains considered are budget constraint and storage capacity constraint. Lagrange Multipliers method with Kuhn-Tucker condition will be used to solve the model. Using this model, the company can determine the order quantity ( Q ), reorder point ( r ) and safety stock ( Ss ) at the optimal point by accomodating purchasing budget and storage capacities of existing raw material. The result of comparison study between this model with the inventory policy by company shows that this model is able to gives an optimal solution. So applying the model, the company is able to save inventory cost 2,42 % every year with consideration storage area capacities. }, url = {https://ejournal.undip.ac.id/index.php/matematika/article/view/266} }
Refworks Citation Data :
Inventory represents the amount of reserved raw material to meet demand of consumers in certain period. If the demand is uncertain, the stock cuold be insufficient or becaming excessive. Therefore, it is required to device an optimal inventory rule which concerning all posible factors. In this paper, a probability inventory model with constraint will be applied on a case of back order policy. The constrains considered are budget constraint and storage capacity constraint. Lagrange Multipliers method with Kuhn-Tucker condition will be used to solve the model. Using this model, the company can determine the order quantity (Q), reorder point (r) and safety stock (Ss) at the optimal point by accomodating purchasing budget and storage capacities of existing raw material. The result of comparison study between this model with the inventory policy by company shows that this model is able to gives an optimal solution. So applying the model, the company is able to save inventory cost 2,42 % every year with consideration storage area capacities.
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