Abstract
Paknejad et al.'s model is considered in this paper. Itemwise multiobjective models for both exponential and uniform lead-time demand are taken and the results are compared numerically both in fuzzy optimization and intuitionistic fuzzy optimization techniques. Objective of this paper is to establish that intuitionistic fuzzy optimizaion method is better than usual fuzzy optimization technique as expected annual cost of this inventory model is more minimized in case of intuitionistic fuzzy optimization method. As a single objective stochastic inventory model where the lead-time demand follows normal distribution and with varying defective rate, expected annual cost is also measured. Finally the model considers for fuzzy cost components, which make the model more realistic, and numerical values for uniform, exponential, and normal lead-time demand are compared. Necessary graphical presentations are also given besides numerical illustrations.
Highlights
In conventional inventory models, uncertainties are treated as randomness and are handled by appealing to probability theory
Necessary graphical presentations are given besides numerical illustrations
In certain situations uncertainties are due to fuzziness and in these cases the fuzzy set theory, originally introduced by Zadeh 1, is applicable
Summary
Uncertainties are treated as randomness and are handled by appealing to probability theory. Hala and EI-Saadani analyzed a constrained single period stochastic uniform inventory model with continuous distributions of demand and varying holding cost. Ouyang and Chang 34 modified Paknejad et al.’s inventory model by relaxing the assumption that the stochastic demand during lead time follows a specific probability distribution and by considering that the unsatisfied demands are partially backordered. Paknejad et al.’s 35 model is considered in this paper, as a single objective stochastic inventory model where the lead-time demand follows normal distribution and with varying defective rate, expected annual cost is measured. Itemwise multiobjective models for both exponential and uniform lead time demand are taken and the results are compared numerically both in fuzzy optimization and intuitionistic fuzzy optimization techniques. The model considers for several fuzzy costs and numerical values for uniform, exponential, and normal lead-time demand are compared.
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