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Pricing and Lot-Sizing Decisions in Retail Industry: A Fuzzy Chance Constraint Approach

Pricing and Lot-Sizing Decisions in Retail Industry: A Fuzzy Chance Constraint Approach

R. Ghasemy Yaghin, S. M. T. Fatemi Ghomi, S. A. Torabi
Copyright: © 2014 |Pages: 22
ISBN13: 9781466649910|ISBN10: 1466649917|EISBN13: 9781466649927
DOI: 10.4018/978-1-4666-4991-0.ch013
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MLA

Yaghin, R. Ghasemy, et al. "Pricing and Lot-Sizing Decisions in Retail Industry: A Fuzzy Chance Constraint Approach." Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems, edited by S. Chakraverty, IGI Global, 2014, pp. 268-289. https://doi.org/10.4018/978-1-4666-4991-0.ch013

APA

Yaghin, R. G., Ghomi, S. M., & Torabi, S. A. (2014). Pricing and Lot-Sizing Decisions in Retail Industry: A Fuzzy Chance Constraint Approach. In S. Chakraverty (Ed.), Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems (pp. 268-289). IGI Global. https://doi.org/10.4018/978-1-4666-4991-0.ch013

Chicago

Yaghin, R. Ghasemy, S. M. T. Fatemi Ghomi, and S. A. Torabi. "Pricing and Lot-Sizing Decisions in Retail Industry: A Fuzzy Chance Constraint Approach." In Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems, edited by S. Chakraverty, 268-289. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4991-0.ch013

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Abstract

Analysis of inventory systems involving market-oriented pricing decisions has recently become an interesting topic in the field of inventory control. Price and marketing expenditure are considered as important elements when selling goods and enhancing revenues by manufacturers. The importance of accounting for uncertainty in such environments spurs an interest to develop appropriate decision making tools to deal with uncertain and ill-defined parameters (such as costs and market function) in joint pricing and lot-sizing problems. In this research, a fuzzy chance constraint multi-objective programming model based on p-fractile approach is proposed to determine the optimal price, marketing expenditure and lot size. Considering pricing, marketing and lot-sizing decisions simultaneously, a possibilistic programming based on necessity measure is considered to handle imprecise data and constraints. Discount strategy as a fuzzy power function of order quantity is determined. After applying appropriate strategies to defuzzify the original possibilistic model, the equivalent multi-objective crisp model is then transformed by a single-objective programming model. A meta-heuristic algorithm is applied to solve the final crisp counterpart.

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