Inventory Model Considering Deterioration, Stock-Dependent and Ramp-Type Demand with Reserve Money and Carbon Emission
Dharmendra Yadav1, S.R. Singh2, Manisha Sarin3
1Dharmendra Yadav*, Department of Mathematics, Vardhaman College, Bijnor, India.
2S.R. Singh, Department of Mathematics, CCS University, Meerut, India. E-mail: firstname.lastname@example.org Manisha Sarin, Research Scholar, Singhania University (Rajasthan) India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 5330-5337 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6696018520/2020©BEIESP | DOI: 10.35940/ijrte.E6696.018520
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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: Now a day, government is more concerned about the environment, so inventory model for deteriorating product for multi-product with partial backlogging is modeled here by considering carbon emission cost under the influence of inflation. It is also assumed buyer have sufficient amount of money to pay the vendor in the beginning of the business but still buyer focus to avail the offer of trade credit offered by vendor. As demand of many products such as fashionable products, cold drinks etc., get stabilized after the acceptance by the market and take the form of ramp-type. So, while developing the model, ramp-type initial stock-dependent demand is considered. As the life time of the product is finite so finite planning horizon is considered here. To obtain the optimal solution, search algorithm is provided. To illustrate and validate the model, numerical example is provided. Further, to study the effect of important parameters, sensitive analysis is also carried.
Keywords: Reserve Money, Multi-Product, Deterioration, Initial Stock-Dependent and Ramp-Type Demand, Partially Backlogging, Carbon Emission.
Scope of the Article: Mobility and Location-dependent services.