Authors:
Pankaj Dutta
and
Madhukar Nagare
Affiliation:
Indian Institute of Technology Bombay, India
Keyword(s):
Inventory, Fuzzy Random Demand, Possibilistic Mean Value, Optimization.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Industrial Engineering
;
Inventory Theory
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Management Sciences
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Symbolic Systems
Abstract:
In the current business scenario, a vital aspect of a realistic inventory model is to accurately estimate the customer demand especially in uncertain environment. Keeping this fact in mind recent trend of research includes uncertain demand, either random or fuzzy. In this paper, we amalgamate both random behavior and fuzzy perception into the optimization setting in modeling an inventory model without backorder. Treating customer demand as fuzzy random variable, we aim at providing an approach of modeling uncertainty that is closer to real situations. In addition, a distinct characteristic of this study is that the decision maker’s degree of optimism is incorporated in this model using possibilistic mean value approach. The objective is to determine the optimal order quantity associated with cost minimization. An illustrative numerical example is presented to clarify the reality of the model.