Optimization of Logistics Cost using a Responsive Optimization Model
This paper presents a supply chain network in which supplier selection, lateral trans-shipment, and vehicle routing can be involved. A Responsive Optimization Model (ROM) comprises several well-known computational intelligence techniques has been proposed to tackle the issue of minimizing the total logistics cost. To validate the proposed approach, other alternative computational intelligence techniques have been used to benchmark the performance. In general, ROM proves to be more efficient and effective comparing with other methods.
Keywords - Responsive Optimization Model, Genetic Algorithms, Logistics Cost, Supply Chain Management