Abstract
In the past, several frameworks and models have been developed in the literatures that addressed the problems and issues of logistics in a supply chain management. In the literature, only few number of variables are taken into consideration in obtaining the solution of the supply chain and most of the research is done on decentralized control strategy only. Such kind of analysis may not give the appropriate solution to the manufacturer among different alternatives. Hence it is necessary to investigate all the variables that affect the performance of the supply chain under different control strategies. The aim of the present work is to compare the centralized and decentralized supply chains to find out which type of supply chain is more advantageous in terms of cost. Two mathematical models were proposed, one for decentralized supply chain and the other for centralized supply chain for comparing the total cost of the two supply chains. In the present work to implement decentralized supply chain an agent based methodology and for centralized supply chain model a linear program model has been used. The author proposed a novel centralized supply chain which considers the same costs and capacities as were considered in the decentralized supply chain. The only difference considered here between centralized and decentralized supply chains is the amount of information sharing. The contribution of this paper is to formulate the centralized and decentralized multi-product multi-period supply chain models and to implement both the models in GAMS software and to obtain the results using NEOS optimization web site. In this paper, 1728 variables for distribution agent and 576 variables for production agent and 192 linking variables, totally 2496 variables are considered which enabled to study the complexity and intricacies of the supply chain. From the results, it was found that a saving of Rs. 4,72,44,400 is possible, if the domestic pump industry considered in the paper follows centralized production–distribution planning. The month-wise production quantity, distribution quantities from factory to distribution centre and from distribution centre to customer, month-wise inventory quantities to minimize the total cost are also obtained.
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