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Integrated inventory problem under trade credit in fuzzy random environment

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Abstract

This paper is concerned with an integrated inventory problem under trade credit where both the demand rate and deteriorating rate are assumed to be uncertain and characterized as fuzzy random variables with known distributions. The objective of this paper is to determine the optimal inventory policy by optimizing simultaneously the replenishment cycle length and trade credit period. At first, three decision criteria are given: (1) expected value criterion, (2) chance-constrained criterion and (3) chance maximization criterion. Then, after building the fuzzy random models based on the above decision criterion, a hybrid intelligent algorithm by integrating fuzzy random simulation and genetic algorithm is employed to deal with these models. At the end, three numerical examples are given to illustrate the benefits of the models and show the effectiveness of the algorithms.

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Acknowledgments

The work was partly supported by the National Natural Science Foundation of China (71071113), a Ph.D. Programs Foundation of Ministry of Education of China (20100072110011), a Foundation for the Author of National Excellent Doctoral Dissertation of P.R. China (200782), Shanghai Pujiang Program, and Shanghai Philosophical and Social Science Program (2010BZH003), the Fundamental Research Funds for the Central Universities.

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  1. School of Business administration, Henan University of Economics and Law, Zhengzhou, 450002, China

    Weihua Xu

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  1. Weihua Xu
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Correspondence to Weihua Xu.

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Xu, W. Integrated inventory problem under trade credit in fuzzy random environment. Fuzzy Optim Decis Making 13, 329–344 (2014). https://doi.org/10.1007/s10700-014-9177-1

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  • DOI: https://doi.org/10.1007/s10700-014-9177-1

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