A Crowdsourced Approach for Supply Chain Network Optimization Using Hub and Spoke Model

Abstract

This study aims to identify and analyze an optimized & efficient supply chain network solved with hub and spoke model using a crowdsourced approach. The main focus of the resulting supply chain is to minimize the total transportation cost and analyze how crowdsourcing affects the whole chain. Hub and spoke distribution paradigm are a form of transport topology optimization in which traffic planners organize routes as a series of "spokes" that connect outlying points to a central "hub". The supply chain network includes a number of manufacturers, suppliers, distributer locations and demand points which need to be located not just randomly but as a result of careful calculation to minimize the overall cost and increase the supply chain surplus. The hub and spoke model is an excellent approach to make the whole system more robust and agile by receiving products from many different origins, consolidating the products, and sending them directly to destinations. Crowdsourcing is the process of obtaining ideas, services or information by soliciting feedback from a large group of people. Here in this report, the effects of crowdsourcing on the supply chain is emphasized by using a linear programming model in MATLAB. The result is evaluated and analyzed for further improvement and practical use.