In the classical inventory models, it was assumed that the buyer pays for the purchased items as they are received from the seller. In practice, however, the seller allows the buyer to settle the account with a delay period. Such a contract has attracted the attention of many researchers and practitioners in recent years. Thus, this paper addresses the researches with delay in payment and presents pertinent information about developments and extensions of such models to provide an up-to-date review of the studies conducted since 1973 and assist in developing the future researches.
Supplier selection is a process by which the firms identify, evaluate, and select the suppliers of their required raw materials. Although this process deploys an overwhelming amount of any firm's financial resources, it would give substantial advantages if suppliers with high value are selected. Moreover, with paying more attention to the exhaustible natural resources and industrial pollution, sustainable supply chain management and sustainable supplier selection have significantly attracted the academic and corporate attention in recent years. Besides conventional criteria such as price and quality, sustainability cares about environmental and ecological respects of industrial activities. Reviewing the literature and considering the previous proposed frameworks for sustainable supply chain, this paper firstly aims at presenting a new structure which considers all of the influential relations between the members of the supply chain. Secondly, based on the new framework, the essential supplier selection measures and criteria are discussed. As the result, the offered scheme can be used by the manufacturers to select the most appropriate suppliers who contribute to the movement of the supply chain toward sustainability.
This paper attempts to obtain the replenishment policy of a manufacturer under EPQ inventory model with backorder. It is assumed here that the manufacturer delays paying for the received goods from the supplier and the items start deteriorating as soon as they are being produced. Based on these assumptions, the manufacturer’s inventory model is formulated, and cuckoo search algorithm is applied then to find the replenishment time, order quantity, and selling price with the objective of maximizing the manufacturer’s total net profit. Besides, the traditional inventory system is shown as a special case of the proposed model in this paper, and numerical examples are given to demonstrate better performance of trade credit. These examples are also used to compare the results of cuckoo search algorithm with genetic algorithm and investigate the effects of the model parameters on its variables and net profit.
This paper considers a centralized supply chain with consignment inventory (CI) system, where a vendor keeps a finished product and supplies it at the same price to multiple buyers. CI is a process where the buyer pays with delay for the goods supplied by the vendor. Considering the time value of money, this study compares two types of delay in payment in CI, which have been rarely considered (real use and order to order). Furthermore, two different metaheuristic algorithms, genetic algorithm (GA) and a hybrid algorithm, containing GA and particle swarm optimization algorithm, are used to maximize the supply chain net profit and calculate the proper values. Finally, a sensitivity analysis is performed to examine the effects of each parameter on the total net profit. Moreover, by applying a paired t-test, a comparison is made between two types of CI system and also between GA and the hybrid algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.