The in-house logistics routing problem
In this work, we consider the internal logistics processes in the car assembling company SEAT S.A (where SEAT is Sociedad Española de Automóviles de Turismo). We focus on the design of the supplying routes from the warehouse toward the workstations along a production line. The in‐house logistics rou...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/46973 |
| Acceso en línea: | http://hdl.handle.net/10230/46973 http://dx.doi.org/10.1111/itor.12965 |
| Access Level: | acceso abierto |
| Palabra clave: | Metaheuristics Integer programming Logistics Combinatorial optimization Automotive industry |
| Sumario: | In this work, we consider the internal logistics processes in the car assembling company SEAT S.A (where SEAT is Sociedad Española de Automóviles de Turismo). We focus on the design of the supplying routes from the warehouse toward the workstations along a production line. The in‐house logistics routing problem (ILRP) can be seen as an extension of the classical vehicle routing problem considering special features such as long‐term fixed routes, unknown orders, backorders, and homogeneous fleet. To solve the ILRP, we propose an integer linear programming (ILP) model and a simulation‐based iterated local search (SimILS) algorithm. We conduct two computational experiments. The first experiment analyzes the methods' performance, and the second experiment compares the SimILS results with the current company's routes, considering real data provided by SEAT S.A. The results show that the SimILS provides the best overall results overcoming both the ILP approach and the current company's solution, leading to a significant improvement in the company's processes. |
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