Optimal retailer's ordering policies in the EOQ model under trade credit financing

2003 ◽  
Vol 54 (9) ◽  
pp. 1011-1015 ◽  
Author(s):  
Y-F Huang

2021 ◽  
Vol 10 (4) ◽  
pp. 14-36
Author(s):  
Mahesh Kumar Jayaswal ◽  
Mandeep Mittal ◽  
Isha Sangal ◽  
Jayanti Tripathi

In this paper, an inventory model has been developed with trade credit financing and back orders under human learning. In this model, it is considered that the seller provides a credit period to his buyer to settle the account and the buyer accepts the credit period policy with certain terms and conditions. The impact of learning and credit financing on the size of the lot and the corresponding cost has been presented. For the development of the model, demand and lead times have been taken as the fuzzy triangular numbers are fuzzified, and then learning has been done in the fuzzy numbers. First of all, the consideration of constant fuzziness is relaxed, and then the concept of learning in fuzzy under credit financing is joined with the representation, assuming that the degree of fuzziness reduces over the planning horizon. Finally, the expected total fuzzy cost function is minimized with respect to order quantity and number of shipments under credit financing and learning effect. Lastly, sensitive analysis has been presented as a consequence of some numerical examples.



2015 ◽  
Author(s):  
Zohreh Molamohamadi ◽  
Rahman Arshizadeh ◽  
Napsiah Ismail


2013 ◽  
Vol 2013 ◽  
pp. 1-22 ◽  
Author(s):  
Yong He ◽  
Hongfu Huang

Trade credit financing is a useful tool in business today, which can be characterized as the agreement between supply chain members such as permissible delay in payments. In this study, we assume that the items have the property of noninstantaneous deterioration and the demand is a function of downstream credit. Then, an EOQ model for noninstantaneous deterioration is built based on the two-level financing policy. The purpose of this paper is to maximize the total average profit by determine the optimal downstream credit period, the optimal replenishment cycle length, and the optimal ordering quantity per cycle. Useful theorems are proposed to characterize the method of obtaining the optimal solutions. Based on the theorems, an algorithm is designed, and numerical tests and sensitive analysis are provided. Lastly, according to the sensitive analysis, managerial insights are proposed.



OPSEARCH ◽  
2010 ◽  
Vol 47 (4) ◽  
pp. 293-310 ◽  
Author(s):  
Chandra K. Jaggi ◽  
Mona Verma




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