Solving packing problems in distribution logistics: models and heuristic algorithms
- Autores: Iván Giménez Palacios
- Directores de la Tesis: Francisco Parreño Torres (dir. tes.), Ramón Álvarez Valdés Olaguíbel (codir. tes.), María Teresa Alonso Martínez (codir. tes.)
- Lectura: En la Universidad de Castilla-La Mancha ( España ) en 2022
- Idioma: inglés
- Tribunal Calificador de la Tesis: Tony Wauters (presid.), Antonio Martínez Sykora (secret.), Eva Vallada Regalado (voc.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: RUIdeRA
- Resumen
In the world of logistics, transport plays a major role. When we talk about transport, we usually think about getting products to customers; however, there are other times when transport comes into action, such as picking up various raw materials to take them to the factory that will finally make the final product, or transporting the products from the factory to the shops for sale. Transport is both a cost to the company and a cause of environmental pollution, so it is important to make efficient use of resources. This efficient use consists of using as much of the vehicles' cargo space as possible so that as few vehicles as possible are used, and also designing the routes so that the total distance travelled is minimised. Less distance travelled means less expense and less pollution, as well as using fewer vehicles, which also means less cost in terms of workers.
In this thesis, I am going to deal with various problems of transport in logistics: firstly, maximising the use of a vehicle by taking into account real constraints in the logistics world, secondly, obtaining the minimum number of trucks necessary to transport all the orders to their respective customers, and finally, a first mile problem, in which the objective is to pick up different products to bring them to the central warehouse, using the smallest number of trucks and travelling the shortest distance possible. Each of these problems is dealt with in a chapter of this thesis, in which the problem is contextualised, defined, modeled using integer linear programming, and solved using exact approaches.
The objective we seek is to obtain good solutions that are useful and applicable to real-life problems. The results confirm the power and flexibility of the algorithms and models. These techniques could serve as a catalyst to even better approaches, with the consequent economic and environmental benefits.
