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2508. Exact approaches for the green commodity-constrained split delivery vehicle routing problem
Invited abstract in session MB-52: Combinatorial optimization approaches for freight deliveries, stream Combinatorial Optimization.
Monday, 10:30-12:00Room: 8003 (building: 202)
Authors (first author is the speaker)
| 1. | Kamyla Ferreira
|
| Production Engineering Department, Federal University of Sao Carlos | |
| 2. | Claudia Archetti
|
| Università degli Studi di Brescia | |
| 3. | Diego Delle Donne
|
| IDS department, ESSEC Bussines School | |
| 4. | Reinaldo Morabito
|
| Dept. of Production Engineering, Federal University of São Carlos | |
| 5. | Pedro Munari
|
| Production Engineering Department, Federal University of Sao Carlos |
Abstract
We address the Green Commodity-Constrained Split Delivery Vehicle Routing Problem (GC-SDVRP), which involves designing efficient and environmentally friendly delivery routes that reduce the carbon dioxide (CO2) emission associated with the transport of multiple commodities. The GC-SDVRP considers that different types of commodities are available at the depot, and each customer has specific demands for different types of commodities. Multiple vehicles may visit a customer to deliver different types of commodities, as long as all commodities of the same type are delivered by the same vehicle, thus reducing customer inconvenience caused by split deliveries. Despite its practical relevance, the green variant of this problem has not been studied in the literature so far. In this talk, we introduce the GC-SDVRP and propose a branch-and-cut approach that is based on the solution of a relaxed formulation that provides a lower bound on the optimal value. Additionally, we adapt two other formulations from the literature. The results of computational experiments using benchmark instances indicate the effectiveness of our proposed method, which outperforms the results of other approaches. Our computational experiments show that minimizing emissions does not necessarily imply minimizing the travel costs, and vice versa. Moreover, it is computationally easier to solve the problem with CO2 emissions than with the traditional objective of minimizing travel costs.
Keywords
- Combinatorial Optimization
- Vehicle Routing
- Branch and Cut
Status: accepted
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