The value of integration of full container load, less than container load and air freight shipments in vendor–managed inventory systems

• Published in: International journal of production economics Vol. 241; p. 108260
• Main Authors: Bertazzi, Luca, Moezi, Sarem Deilami, Maggioni, Francesca
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-11-2021
• Subjects: Air freight; Full container load (FCL); Less than container load (LCL); Mixed integer linear programming; Vendor–managed inventory (VMI); Worst-case analysis; Vendor–managed inventory (VMI); Worst-case analysis; Air freight; Full container load (FCL); Mixed integer linear programming; Less than container load (LCL)
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2021.108260

We address a long–haul transportation problem of delivering a set of products from a producer to a customer, where Full Container Load (FCL) shipments on one side and Less than Container Load (LCL) or Air Freight shipments on the other side are integrated. A Vendor-Managed Inventory (VMI) approach is used: a decision-maker has to find a periodic shipping policy that minimizes the sum of transportation cost and inventory cost, both at the producer and at the customer. This problem is defined at the tactical level implying that the initial inventory levels at the producer and at the customer are not data, but decision variables. For this problem we formulate a Mixed Integer Linear Programming model and prove its computational complexity. Furthermore, we introduce the concept of Value of Integration of FCL and LCL/Air Freight shipments and prove performance bounds to show that the integration of FCL and LCL/Air Freight shipments can lead to significant cost savings, both in the worst case and on average. Systematic computational experiments are finally carried out.
•Introducing lead times in integrated Vendor-Management Inventory systems with given shipping frequencies.•Providing the value of integrating FCL, LCL/Air Freight shipments, in the worst case and on average.•Proving the complexity of the problem.