Joint replenishment problem with quantity discounts

Wang, Feifei (2020) Joint replenishment problem with quantity discounts. [Dissertation (University of Nottingham only)]

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In the joint replenishment process, suppliers tend to provide various

kinds of quantity discounts to retailers and it could result in some

substantial cost saving. Previous studies have realized the

importance of quantity discounts in joint replenishment problems and

researches have paid the most attention to the JRP and JRP of a single

product with multi quantity discounts or multi-products with a single

quantity discount. However, they ignored the fact that in reality,

suppliers will offer different kinds of quantity discounts for different

products in the joint replenishment and vendors would not only buy

one kind of product from suppliers. Therefore, this dissertation aims

at finding the effects of different quantity discounts on multi-item

joint replenishment.

In the dissertation, the mathematical JRP model, considering two

mainly used discounts: the all-unit discount, the incremental discount,

is constructed to build the connection between the total cost,

replenishment time intervals and order frequencies. After that, the

corresponding heuristic algorithms are proposed to solve the model

and find the optimal solutions, minimum total cost, for JRP under

different discounts. A computational experiment with a case of five

products is made to find the features and differences of JRP with

different quantity discounts.

The results of this study make contributions to the gap in the

literature. Also, it has the practical value that suppliers and retailers

could utilize one model or algorithms to obtain the optimal solution

and make a proper decision under different quantity discounts,

instead of transforming between different models. And the

summarized characteristics and differences can help people better

understand when to use different quantity discounts.

Item Type: Dissertation (University of Nottingham only)
Depositing User: WANG, Feifei
Date Deposited: 13 Apr 2023 13:01
Last Modified: 13 Apr 2023 13:01

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