| Title |
An optimization framework for efficient and sustainable logistics operations via transportation mode optimization and shipment consolidation: A case study for GE Gas Power |
| ID_Doc |
66447 |
| Authors |
Camur, MC; Bollapragada, S; Thanos, AE; Dulgeroglu, O; Gemici-Ozkan, B |
| Title |
An optimization framework for efficient and sustainable logistics operations via transportation mode optimization and shipment consolidation: A case study for GE Gas Power |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.eswa.2024.124304 |
| Abstract |
General Electric (GE) Gas Power, a leading manufacturer of gas and steam turbines, manufactures and installs these turbines in power generation plants worldwide. They source components for these turbines from suppliers globally and transport these components to manufacturing and assembly locations in the United States using various modes of transportation, including ocean, air, and ground. These transportation options have different lead times and costs. The challenge lies in identifying the most cost-effective solution that meets the assembly requirements, given the high volume of shipments and the complexity of the intermodal freight network. To address this challenge, a customized, multi -period (dynamic), multi -commodity network flow model and a novel heuristic approach with a rolling time horizon are developed. This model incorporates consolidation and storage options at intermediate nodes, allowing the business to optimize its shipments. This research addresses a unique real -world logistics problem and offers an optimization model together with an efficient solution approach for industry. Computational experiments indicate that the heuristic approach proposed can yield results closely aligned with those produced by state -of -the art commercial solvers. Furthermore, the experiments show the criticality of full container load shipments in achieving substantial cost -saving in global shipments. |
| Author Keywords |
Network optimization; Multi-period multi-commodity network flow; Shipment consolidation; Supply chain and logistics; Intermodal transportation |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001248609000001 |
| WoS Category |
Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science |
| Research Area |
Computer Science; Engineering; Operations Research & Management Science |
| PDF |
https://arxiv.org/pdf/2212.03662
|