Authors :
Md. Rukonuzzaman; Aminur Rahman Khan
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
http://tinyurl.com/md3vrzdm
Scribd :
http://tinyurl.com/hn9deabd
DOI :
https://doi.org/10.5281/zenodo.10731514
Abstract :
The conventional inventory model, known as
the crisp inventory model, assumes that parameters have
precise and certain values. However, in real-world
scenarios, it is observed that uncertainties or
imprecisions in the environment prevent the exact
definition of all parameters. To address this uncertainty,
fuzzy set theory may be applied, providing decision-
makers with mathematical tools to formulate inventory
models that reflect real-world conditions. This study
explores two inventory models: a traditional crisp model
and its corresponding fuzzy counterpart. The focus is on
a non-instantaneous deteriorating item with time-
sensitive demand under a unit price discount policy,
considering fully backlogged shortages and
incorporating salvage value for deteriorated units. In the
fuzzy environment, parameters such as demand,
deterioration rate, salvage, and cost components like
ordering cost, holding cost, and shortages cost are
represented as triangular fuzzy numbers. The Signed
distance method is utilized for defuzzification of fuzzy
outputs. Numerical examples are offered to justify and
compare the anticipated crisp and fuzzy models.
Additionally, a sensitivity analysis for the fuzzy model is
conducted to provide managerial implications.
Keywords :
Crisp inventory model,Fuzzy inventory model, Non-instantaneous,Time-sensitive demand, Price discount policy, Fully backlogged shortages, Salvage value, Triangular fuzzy number,Defuzzification, Signed distance method.
The conventional inventory model, known as
the crisp inventory model, assumes that parameters have
precise and certain values. However, in real-world
scenarios, it is observed that uncertainties or
imprecisions in the environment prevent the exact
definition of all parameters. To address this uncertainty,
fuzzy set theory may be applied, providing decision-
makers with mathematical tools to formulate inventory
models that reflect real-world conditions. This study
explores two inventory models: a traditional crisp model
and its corresponding fuzzy counterpart. The focus is on
a non-instantaneous deteriorating item with time-
sensitive demand under a unit price discount policy,
considering fully backlogged shortages and
incorporating salvage value for deteriorated units. In the
fuzzy environment, parameters such as demand,
deterioration rate, salvage, and cost components like
ordering cost, holding cost, and shortages cost are
represented as triangular fuzzy numbers. The Signed
distance method is utilized for defuzzification of fuzzy
outputs. Numerical examples are offered to justify and
compare the anticipated crisp and fuzzy models.
Additionally, a sensitivity analysis for the fuzzy model is
conducted to provide managerial implications.
Keywords :
Crisp inventory model,Fuzzy inventory model, Non-instantaneous,Time-sensitive demand, Price discount policy, Fully backlogged shortages, Salvage value, Triangular fuzzy number,Defuzzification, Signed distance method.