Development of Inventory Models under Uncertain Environment

Abstract

Traditional inventory models are developed with precisely known and constant parametric values. However, in reality, one or more parameters (like demand, holding cost, ordering cost etc.) of an inventory model often deviate slightly from one cycle to another cycle and exhibit uncertainty to certain extent over a planning horizon. This uncertainty raises challenges for applying traditional inventory models in practice. To cope up with quantitatively with uncertainty in decision making related to inventory policy, in this thesis, we framed some inventory models with stochastic, fuzzy or fuzzy stochastic environment. newlineIn this thesis, we have formulated inventory models (3 models) with vendor-buyer system under stochastic and fuzzy stochastic environment. Besides, we have presented (1 model) Continuous review inventory model with reducing lost sales rate under fuzzy stochastic demand and variable lead time. Further, we have developed production inventory model (2 models) under mand#955; measure which is linear combination of Possibility measure and Necessity measure. Moreover, we have established optimal pricing and inventory policies for non-instantaneous deteriorating items (4 models) under stochastic as well as fuzzy framework. newlineAttempt has been made to make the above models more realistic and illustrated numerically with some hypothetical data. Though the data used in this thesis are not real life data, the models can be used by the inventory / operation research practitioners to solve their present problems in the field of inventory and production. newline newline