Informatics Publishing Limited

S. Nagabhushana ¹, N. S. Narahari ¹, C. K. Nagendra Guptha ¹

Affiliations
1 Department of Industrial Engineering and Management, R V College of Engineering, Bengaluru – 560 059, Karnataka, IN

Abstract

Tons of vegetables go to waste as they are produced in excess than the current demand and go to waste in storage units without any customer to buy them. The objective of the study is to develop a model that helps in effective distribution of vegetable yield demand. Prediction model was developed using regression analysis to find out the future yield so that the farmer can plan the distribution of his produce. Second phase of the study was aimed at reducing transportation using cost integer programming from distributors to retailers while meeting the demand at the same time. The developed model can predict the future yield value which will be closer to the actual yield value. Future demand can also be determined which will be closer to the actual demand. Based on the yield generated and demand comparison, decision can be incorporated in the distribution of vegetables by the farmer to different regions. If the demand is more than yield, tapping of other sources is done. If the demand is lesser, the part of the yield can be sent to other towns and cities where demand has not been met. Food waste problem can be tackled at the source itself by using this model. Wastage can be reduced considerably which is one of the final benefits that will contribute to the societal welfare and development. The integer programming model done for optimizing the cost of distribution provides a feasible solution to the distributors and retailers and satisfying the demand at the same time. Thus, total cost can be minimized without affecting the efficiency of distribution. Distributors and retailers can optimize their distribution effectively while minimizing the transportation cost as much as possible without affecting the demand.

Keywords

Food Supply Chain, Integer Programming, Linear Regression, Winter’s Demand Forecast Model, Yield Prediction Model.

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B. Raghavendra Prasad ¹, Dipankar Banerjee ¹, Jagdev Singh ¹, S. Nagabhushana ¹, Amit Kumar ¹, P. U. Kamath ¹, S. Kathiravan ¹, Suresh Venkata ¹, N. Rajkumar ¹, V. Natarajan ¹, Madhur Juneja ¹, Pawan Somu ¹, Vaibhav Pant ¹, Nigar Shaji ², K. Sankarsubramanian ², Asit Patra ³, R. Venkateswaran ⁴, Abhijit Avinash Adoni ², S. Narendra ², T. R. Haridas ⁵, Shibu K. Mathew ⁶, R. Mohan Krishna ², K. Amareswari ², Bhavesh Jaiswal ²

Affiliations
1 Indian Institute of Astrophysics, 2nd Block, Koramangala, Bengaluru 560 034, IN
2 ISRO Satellite Centre, Old Airport Road, Vimanapura Post, Bengaluru 560 017, IN
3 Space Applications Centre, Jodhpur Tekra, Ambawadi Vistar, P.O., Ahmedabad 380 015, IN
4 Laboratory for Electro-Optics Systems, First Phase, Peenya Industrial Estate, Bengaluru 560 058, IN
5 ISRO Inertial Systems Unit, Vattiyoorkavu PO, Thiruvananthapuram 695 013, IN
6 Udaipur Solar Observatory, Near Fatehpur Lake, Shilpgram, Udaipur 313 004, IN

Abstract

Solar coronagraph mimics total solar eclipse by blocking the solar disk and enabling the observation of extended coronal atmosphere of the Sun. Visible Emission Line Coronagraph (VELC), on-board Aditya-L1 space mission, is an internally occulted solar coronagraph capable of simultaneous imaging, spectroscopy and spectro-polarimetry close to the solar limb. This payload is designed to study the coronal plasma and heating of the solar corona. Studying development, dynamics and origin of coronal mass ejections and measurement of coronal magnetic fields over active regions are other important science goals. VELC is designed to image the solar corona at 500 nm with an angular resolution of 5" over a field of view (FOV) of 1.05-3 R_o. It also facilitates simultaneous multi-slit spectroscopy at three emission lines, viz. Fe XIV (530.3 nm), Fe XI (789.2 nm) and Fe XIII (1074.7 nm) with a spectral resolution of 28 , 31 and 202 mÅ/pixel respectively, over an FOV of 1.05-1.5 R_o. The payload has a dual-beam spectro-polarimetry channel for magnetic field measurements at 1074.7 nm.

Keywords

Coronagraph, Coronal Mass Ejection, Payload, Solar Corona.

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