Dynamic pricing model and algorithm for perishable products with fuzzy demand

Yu Xiong, Gendao Li, Kiran Jude Fernandes

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.
Original languageEnglish
Pages (from-to)758-774
Number of pages17
JournalApplied Stochastic Models in Business and Industry
Issue number6
Publication statusPublished - 2010

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