Designing a fuzzy inference system to choose the product portfolio of pharmaceutical
Subject Areas : Supply Chain Management
Mohamadali Afsharkazemi
1
,
Ali Barkhordari
2
*
1 - Industrial Management, Faculty of Economics and Management, Islamic Azad University, Science and Research branch, Tehran, Iran
2 -
Keywords: product selection, fuzzy inference, pharmaceutical ,
Abstract :
Introduction: Selecting new pharmaceutical products from among successful and best-selling products is a serious and important matter. A point that seems to be problematic in the product portfolio development process is the analysis of actual and potential competitors and the success rate of new products in gaining market share. The aim of this article is to introduce and design a fuzzy inference system for evaluating product portfolios for production in pharmaceutical companies.
Methodology: For this purpose, using a fuzzy inference system, the product portfolios in Iranian pharmacies were examined during the period 1400-1403.A fuzzy inference system is a mapping from input to output space that is implemented using membership functions and fuzzy rules. In fact, it is a system that implements human experiences with membership functions and fuzzy rules and is a general method for combining knowledge, intelligent technology, control and decision-making. The most important fuzzy inference algorithms are the Mamdani and Takagi Sugeno inference algorithms, which have the most applications. In this study, the Mamdani fuzzy inference system was used to identify selected products in terms of three criteria: profit margin, market share and company revenue share.
.Results and Discussion: The results showed that with the fuzzy expert system, the existence of errors in decision-making related to the selection of a product portfolio from among the mass of products that can be produced is significantly reduced. Therefore, the fuzzy inference system is an efficient and suitable tool for evaluating products and forming a product portfolio in the pharmaceutical industry.
Conclusion: Based on the results, it is recommended to use a fuzzy inference system in developing companies'product portfolios, especially in the researched statistical population, namely pharmaceutical companies in our country, Iran.
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