Modeling and solving a one supplier multi-vehicle production-inventory-distribution ptoblem xith clustered retailers, ISSN/ISBN 0268-3768 / 1433-3015

Citation:

Ahmed, Senoussi, Mouss kinza Nadia, and Dauzere-Peres. 2015. “Modeling and solving a one supplier multi-vehicle production-inventory-distribution ptoblem xith clustered retailers, ISSN/ISBN 0268-3768 / 1433-3015”. INT J ADV MANUF TECH Volume 85 ( Issue 5–8) : pp 971–989.

Abstract:

This paper considers a supply chain management problem which integrates production, inventory, and distribution decisions. The supply chain is composed of one supplier production facility and several retailers located in a given geographic region. The supplier is responsible for the production and the replenishment of the inventory of retailers, in a vendor managed inventory (VMI) context. The distance between retailers is negligible compared to the distance between the supplier and the retailers’ region. Thus, for each vehicle, there is a major fixed cost for traveling to the cluster of retailers and a minor fixed cost for visiting each individual retailer. The problem consists of determining quantities to be produced, quantities to be delivered to retailers, vehicles to be used, and retailers to be serviced by each vehicle. This problem is an extension of the one warehouse multi-retailer problem with the consideration of production planning and storage and vehicle capacity limitations in addition to fixed vehicle utilization costs and retailer servicing costs. The objective is to minimize a total cost composed of production, transportation, and inventory holding costs at the supplier and at the retailers. Two mixed integer linear programming formulations are proposed and six families of valid inequalities are added to strengthen these formulations. Two of these families are new and the others are adapted from the literature. The numerical results show that the valid inequalities considerably improve the quality of the formulations. Moreover, the parameters that influence the most computational times are analyzed

Publisher's Version