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mahmoudi, A., shavandi, H., nouhi, K. (2012). Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm. Journal of Optimization in Industrial Engineering, 5(10), 1-9.
amin mahmoudi; hassan shavandi; khashayar nouhi. "Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm". Journal of Optimization in Industrial Engineering, 5, 10, 2012, 1-9.
mahmoudi, A., shavandi, H., nouhi, K. (2012). 'Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm', Journal of Optimization in Industrial Engineering, 5(10), pp. 1-9.
mahmoudi, A., shavandi, H., nouhi, K. Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm. Journal of Optimization in Industrial Engineering, 2012; 5(10): 1-9.

Analysing Price, Quality and Lead Time Decisions with the Hybrid Solution Method of Fuzzy Logic and Genetic Algorithm

Article 1, Volume 5, Issue 10, Winter and Spring 2012, Page 1-9  XML PDF (7419 K)
Document Type: Original Manuscript
Authors
amin mahmoudi 1; hassan shavandi2; khashayar nouhi3
1Department of Industrial and mechanical Engineering, Islamic Azad University, Qazvin branch, Qazvin, Iran
2Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
3Department of Industrial and mechanical Engineering, Islamic Azad University, Qazvin branch, Qazvin,
Abstract
In this paper, the problem of determining the quality level, lead time for order delivery and price of a product produced by a manufacturer is considered. In this problem the demand for the product is influenced by all three decision variables: price, lead time and quality level. To formulate the demand function, a fuzzy rule base that estimates the demand value based on the three decision variables is developed. To do
so, the linguistic knowledge of experts in the form of if-then rules is used to establish the fuzzy system. Moreover, in order to solve the problem, a genetic algorithm integrating the fuzzy rule base is proposed. Finally, to support the validity of the proposed solution, a numerical study is provided.
Keywords
Fuzzy Logic; Linguistic variable; Genetic algorithm; Pricing; Quality level; Lead time
Main Subjects
Design of Experiment
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