Manuscript Title:

OPTIMIZATION OF FUZZY INTERVALUED FUNCTION IN MEDICINAL MANUFACTURING AND STOCK APPROACHES: REFINEMENT FOR A PHARMA COMPANIES

Author:

K. KALAIARASI, MEENAKSHI K, HANUMANTHA RAVI P V N

DOI Number:

DOI:10.5281/zenodo.10690868

Published : 2024-02-10

About the author(s)

1. K. KALAIARASI - Assistant Professor, PG and Research Department of Mathematics, Cauvery College for Women (Autonomous), (Affiliated to Bharathidasan University), Tiruchirappalli. D.Sc. (Mathematics) Researcher, Srinivas University, Surathkal, Mangaluru, Karnataka.
2. MEENAKSHI K - Professor, Department of Mathematics VTU (RC), CMR Institute of Technology, Kundalahalli, Bengaluru.
3. HANUMANTHA RAVI P V N - Professor, Department of Mathematics VTU (RC), CMR Institute of Technology, Kundalahalli, Bengaluru.

Full Text : PDF

Abstract

Each section of the healthcare industry should make an effort to supply excellent service for medical supplies and implement efficient inventory management procedures. Inappropriate drug use and medication deficiencies can hurt individuals & cost businesses money. Because they haven't thought about how pharmaceuticals are handled, delivered, and used to save lives and enhance health, many health systems and hospitals struggle to meet these objectives. Research is necessary to comprehend how the health care sector operates and to develop instruments for decision of pharmaceuticals, improved patient, and public health. The pharmaceutical industry is crucial to the healthcare sector because of the expensive prices of the products and the stringent storage and control requirements. Both buying and distributing can be expensive. Pharmaceutical management must be successful in order to ensuring that goods are always available offered to the relevant customers at the appropriate time, at the acceptable price, and in a good quality. In this study, model’s extended to include the manufacturing rate, screening rate, holding cost & selling cost of pharmaceutical company's product as trapezoidal fuzzy values in the overall cost. 


Keywords

Kuhn Tucker Techniques, Total Cost, Fuzzy Logic, Numerical Values, Arithmetic Operations, Python Programming.