Development of genetic algorithm on multi-vendor integrated procurement-production system under shared transportation and just-in-time delivery system

One of the well-known inventory control techniques utilized in the supply chain is integrated inventory model. Recently, previous research [Z.X Chen and B.R Sarker, Multi-vendor integrated procurement-production system under shared transportation and just-in-time delivery system, Journal of the Operational Society 61 (2010) 1654-1666] have developed an integrated model to synchronize the production flow from multi-vendor to manufacturer through shared transportation. However, the model is complex to find the optimal solution. Because of these complexities, simplifications of the model are often based on limiting assumptions. Since the model is a non-linear integer programming type, this paper addresses genetic algorithm to overcome the limitations to find batch production lot size of vendors and manufacturer, delivery quantities and number of deliveries from different vendors to the manufacturer in order to minimize total cost of all parties involved in the supply chain. Furthermore, a numerical example is presented to illustrate the results.