Abstract
In order to deal with a problem with incomplete information or in uncertain and ambiguous situation, fuzzy programming and chance-constrained programming technique have been developed. This paper presents a chance constrained programming approach to a single-period inventory model in which the storage space is treated as fuzzy random variable. Here the uncertain parameter is considered as log-normally distributed fuzzy random variable whose mean and variance are type-1 fuzzy number. We present a solution procedure for solving single-period inventory fuzzy probabilistic model (SPIFPM) in which the storage space in the constraint is a FRV considered as log-normal distribution. Also the purchasing cost, selling price, salvage value are type-1 fuzzy numbers and the demand is a FRV whose mean and variance are type-1 fuzzy numbers in the objective function of the given model. A mathematical technique has been developed to transform the fuzzy model into a crisp model and a numerical example is given to explain the methodology.
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Sahoo, A., Dash, J.K. (2019). Solving a Chance-Constrained Single-Period Inventory Model with Type-1 Fuzzy Set. In: Tripathy, A., Subudhi, R., Patnaik, S., Nayak, J. (eds) Operations Research in Development Sector. Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-13-1954-9_2
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DOI: https://doi.org/10.1007/978-981-13-1954-9_2
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