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Can I read A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows on EtoBox?
A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows by Rodolfo G. Dondo; Jaime Cerdá is a Engineering article available to read on EtoBox.
What is A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows about?
One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.
Who reads A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- Rodolfo G. Dondo; Jaime Cerdá
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0098-1354)
- Published
- 2009
- Language
- EN
- Field
- Engineering (Physical Sciences)