An Alternative Method to Reduce Medicine Costs By Minimizing Transportation Overheads
Ruchi Gupta1, Mukesh Sahu2, Nikita Gulati3, Komal4, Diksha Jasrotia5
1Ruchi Gupta, Department of Mathematics, Manav Rachna University, Faridabad, India
2Mukesh Sahu Department of Electronics and Communication Engineering, Guru Tegh Bahadur Institute of Technology, New Delhi.
3Nikita Gulati Department of Mathematics, Manav Rachna University, Faridabad (Haryana), India.
4Komal Department of Mathematics, Manav Rachna University, Faridabad (Haryana), India.
5Diksha Jasrotia, Department of Mathematics, Manav Rachna University, Faridabad (Haryana), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 91-94 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6343048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we will introduce a new method to reduce medicine costs by Minimizing transportation Overheads. We have named this method the “Geometric mean method”. This method which we have devised provides a more optimal and efficient solution to the problems when compared to many methods like NWCM, BCM, MM method, Vogel’s method, Average total Opportunity Cost and many more. Using this method, we can provide solutions for logistical issues faced in various fields. Here, we will focus mainly in the field of pharmacy and healthcare. Today, we are living in a world where diseases are on the rise. So, by reducing the total expenditure on logistics, it will lead to a net profit to the End customer. Also one of the reasons why this method is beneficial is that it determines the exact average while dealing with ratios and is less affected by sampling fluctuations. So, this method gives more efficient results. The procedure and working of this method is explained in a simple and understandable language. Also the method contains less iteration which implies that the method is not too lengthy. In order to deal with the transportation Overheads, we have approached a new method and several examples showing the difference in costs which has been discussed in the chapter will provide a detailed understanding to the concept. Here we will give a detailed comparison between the various methods in a mathematical and graphical manner. The proposed method proves out to be very useful and gives optimal solutions to the problems in contrast to existing available methods.
Keywords: Feasible Solution, Optimization, Allocation
Scope of the Article: Discrete Optimization