Routing with Early Ordering for Just-In-Time Manufacturing Systems

Abstract

Parts required in Just-In-Time manufacturing systems are usually picked up from suppliers on a daily basis, and the routes are determined based on average demand. Because of high demand variance, static routes result in low truck utilization and occasional overflow. Dynamic routing with limited early ordering can significantly reduce transportation costs. An integrated mixed integer programming model is presented to capture transportation cost, early ordering inventory cost and stop cost with the concept of rolling horizon. A four-stage heuristic algorithm is developed to solve a real-life problem. The stages of the algorithms are: determining the number of trucks required, grouping, early ordering, and routing. Significant cost savings is estimated based on real data.