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International Journal of Innovation and Scientific Research
ISSN: 2351-8014
 
 
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PRICING RULE FOR NON-REVERSIBLE PROCESSING (PR-NRP) BY USING MATHEMATICAL TOOLS IN BIAS LINEARIZATION SLOPE ADJUSTMENT


Volume 18, Issue 1, September 2015, Pages 122–135

 PRICING RULE FOR NON-REVERSIBLE PROCESSING (PR-NRP) BY USING MATHEMATICAL TOOLS IN BIAS LINEARIZATION SLOPE ADJUSTMENT

Abdul Mannan1, Nasir uddin Khan2, and Mushtaq Hussain3

1 Department of Mathematics, University of Karachi, Karachi, Sindh, Pakistan
2 Department of Mathematics, University of Karachi, Karachi, Sindh, Pakistan
3 Dean of Sciences, Newport University, Karachi, Sindh, Pakistan

Original language: English

Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


In the scenario of price complexity the industrial process such as electricity generation or (CNG) liquid fuel production or such business process that required a very strong policy of pricing to accommodate the consumer demand against production.
A new mathematical tool suggest a logical pricing rule for such non-reversible business process by using mathematical distribution and costing algorithms the short fall of production due to high cost of generating parameters is compensated by using linear distribution and economize utility of resources. The major share of the consumer parameter is isolated by using non-production parameters of generation into direct relation of pricing the mathematical caricature used for simulation on the business model will be analyze by using mathematical tools for a definite workable pricing rule.


Author Keywords: Pricing rule, non-reversible process, linear distribution, consumer parameters, profitability, pricing demand consumer parameters.


How to Cite this Article


Abdul Mannan, Nasir uddin Khan, and Mushtaq Hussain, “PRICING RULE FOR NON-REVERSIBLE PROCESSING (PR-NRP) BY USING MATHEMATICAL TOOLS IN BIAS LINEARIZATION SLOPE ADJUSTMENT,” International Journal of Innovation and Scientific Research, vol. 18, no. 1, pp. 122–135, September 2015.