scholarly journals Supply Chain Model with Stochastic Lead Time, Trade-Credit Financing, and Transportation Discounts

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Sung Jun Kim ◽  
Biswajit Sarkar

This model extends a two-echelon supply chain model by considering the trade-credit policy, transportations discount to make a coordination mechanism between transportation discounts, trade-credit financing, number of shipments, quality improvement of products, and reduced setup cost in such a way that the total cost of the whole system can be reduced, where the supplier offers trade-credit-period to the buyer. For buyer, the backorder rate is considered as variable. There are two investments to reduce setup cost and to improve quality of products. The model assumes lead time-dependent backorder rate, where the lead time is stochastic in nature. By using the trade-credit policy, the model gives how the credit-period would be determined to achieve the win-win outcome. An iterative algorithm is designed to obtain the global optimum results. Numerical example and sensitivity analysis are given to illustrate the model.

Author(s):  
Sumon Sarkar ◽  
B. C. Giri

The paper investigates a two-echelon production-delivery supply chain model for products with stochastic demand and backorder-lost sales mixture under trade-credit financing. The manufacturer delivers the retailer's order quantity in a number of equal-sized shipments. The replenishment lead-time is such that it can be crashed to a minimum duration at an additional cost that can be treated as an investment. Shortages in the retailer's inventory are allowed to occur and are partially backlogged with a backlogging rate dependent on customer's waiting time. Moreover, the manufacturer offers the retailer a credit period which is less than the reorder interval. The model is formulated to find the optimal solutions for order quantity, safety factor, lead time, and the number of shipments from the manufacturer to the retailer in light of both distribution-free and known distribution functions. Two solution algorithms are provided to obtain the optimal decisions for the integrated system. The effects of controllable lead time, backorder rate and trade-credit financing on optimal decisions are illustrated through numerical examples.


Author(s):  
Monami Das Roy ◽  
Shib Sankar Sana

This study explores simultaneous reduction strategies of lead time and setup cost in a two-stage supply chain model under trade-credit financing. Lead time depends on avariable production rate and lot size. It consists of setup, production, and transportation time which are shortened to reduce lead time. Although double safety factors are considered to avoid stock-out; but still backorders take place as the demand during the lead time is stochastic.Setup cost is reduced by including an extra investment cost. In addition, the vendor offers a fixed credit period to the buyer to settle the account. The objective is to minimize the integrated expected total cost and optimize the order quantity, number of deliveries, setup and transportation time, setup cost, safety factor for the first batch, and the production rate. A multi-variable optimization technique is used for these purposes. Furthermore, a numerical example together with managerial insights is provided for the establishment and applicability of the proposed model.The numerical results show that the introduction of setup cost reduction and trade-credit financing along with lead time reduction is more beneficial by means of integrated expected total cost reduction.


2020 ◽  
Vol 8 (5) ◽  
pp. 5113-5117

This study focuses on an integrated vendor-buyer supply chain model where the lead-time and ordering cost reduction act dependently. The lead time demand of a product follows a normal distribution. The manufacturing process is imperfect. During production run time, a certain percentage of defective products are produced, which are immediately reworked. Trade-credit financing has been taken into consideration. The goal of this study is to minimize the joint total expected cost by providing an inter-dependent reduction strategy of lead-time and ordering cost along with the determination of the optimal values of lead-time, number of deliveries, order lot size, ordering cost, lead-time crashing cost, and the joint total expected cost. A solution algorithm and a numerical example are presented to illustrate and establish the integrated model. This model can be used in textiles, automobiles and computers industries.


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