Title: Two warehouse inventory models of breakable items with stock dependent demand under trade credit policy with respect to both supplier and retailer

Authors: Bijoy Krishna Debnath; Pinki Majumder; Uttam Kumar Bera

Addresses: Department of Mathematics, National Institute of Technology, Agartala, Jirania - 799055, West Tripura, India ' Department of Mathematics, National Institute of Technology, Agartala, Jirania - 799055, West Tripura, India ' Department of Mathematics, National Institute of Technology, Agartala, Jirania - 799055, West Tripura, India

Abstract: For the first time, this study deals with a nonlinear form of breakability in two-warehouse inventory control for stock dependent demand. Moreover, this paper relates to two warehouse inventory policies with continuous release patterns along with two-level credit periods with respect to both supplier and retailer. Since per unit selling price is greater than that of purchasing cost, a new approach is introduced for payment to the wholesaler for the amount remaining after the credit period. Here, the retailer earns the required amount before the end of the business period and clears his due as soon as it is available. The sales and interest for the remaining period are deposited for maximising profit and consequently minimising the total inventory cost. Here, the decision variables are business periods for rented and market warehouse. The model has been developed as a cost minimisation problem with respect to the retailer and wholesaler and optimised using the nonlinear optimisation technique - generalised reduced gradient method (LINGO 13.0). The optimal solution has been exemplified numerically and graphically in this study of approach.

Keywords: EPQ model; two-warehouse; trade credit; continuous release pattern; alternative approach of payment; nonlinear breakability.

DOI: 10.1504/IJLSM.2018.094934

International Journal of Logistics Systems and Management, 2018 Vol.31 No.2, pp.151 - 166

Received: 04 Feb 2017
Accepted: 25 Mar 2017
Published online: 27 Sep 2018 *

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