1215. The Distributionally Robust Cyclic Inventory Routing
Invited abstract in session TB-58: Inventory Routing, stream Vehicle Routing and Logistics.
Tuesday, 10:30-12:00Room: Liberty 1.13
Authors (first author is the speaker)
| 1. | Menglei Jia
|
| Department of Management Science, Shanghai Jiao Tong University | |
| 2. | Albert Schrotenboer
|
| Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology | |
| 3. | Ahmadreza Marandi
|
| Industrial Engineering, Eindhoven University of Technology | |
| 4. | Feng Chen
|
| Shanghai Jiao Tong University |
Abstract
This study addresses the cyclic inventory routing problem (CIRP), where the proposed cost-optimal solution on joint inventory replenishment and vehicle routing is cyclic, enabling repetitive execution over an infinite planning horizon. We allow ambiguity in the probability distribution of the stochastic demands faced by retailers, leading to a min-max expectation structure for inventory cost optimization and chance constraints structure that ensures the delivery plan in each period is feasible with a given probability. To solve this challenging problem, we perform exhaustive mathematical analysis to simplify the structures, enabling a tailored nested branch-and-price framework that decomposes the problem into mixed-integer linear subproblems solvable with standard optimization techniques. Within this nested framework, we propose three service policies that unify existing CIRP approaches and extend state-of-the-art inventory policies from the inventory management literature. Extensive experiments validate the effectiveness of our distributionally robust CIRP using both synthetic datasets and real-world data from an industry partner.
Keywords
- Logistics
- Vehicle Routing
- Stochastic Optimization
Status: accepted
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