Flexibility and Complexity in Periodic Distribution Problems

Abstract

In this paper, we explore trade-offs between operational flexibility and operational complexity in periodic distribution problems. We consider the gains from operational flexibility in terms of vehicle routing costs and customer service benefits, and the costs of operational complexity in terms of implementation difficulty. Periodic distribution problems arise in a number of industries, including food distribution, waste management and mail services. The period vehicle routing problem (PVRP) is a variation of the classic vehicle routing problem in which driver routes are constructed for a period of time; the PVRP with service choice (PVRP-SC) extends the PVRP to allow service (visit) frequency to become a decision of the model. While introducing operational flexibility in periodic distribution systems can increase efficiency, it poses three challenges: the difficulty of modeling this flexibility accurately; the computational effort required to solve the problem as modeled with such flexibility; and the complexity of operationally implementing the resulting solution. This paper considers these trade-offs between the system performance improvements due to operational flexibility and the resulting increases in operational and computational complexity as they relate to periodic vehicle routing problems. In particular, increasing the operational complexity of driver routes can be problematic in industries where some level of system regularity is required. As discussed in the paper, recent work in the literature suggests that dispatching drivers consistently to the same geographic areas results in driver familiarity and improved driver performance. Additionally, having the same driver visit a customer on a continual basis can foster critical relationships. According to UPS, such driver-customer relationships are a key competitive advantage in its package delivery operations, attributing 60 million packages a year to sales leads generated by drivers. In this paper, we develop a set of quantitative measures to evaluate the trade-offs between flexibility and complexity.