Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/43618
Título: | Integrating packing and distribution problems and optimization through mathematical programming | Autores/as: | Miguel, Fabio Frutos, Mariano Tohmé, Fernando Méndez, Máximo |
Clasificación UNESCO: | 120304 Inteligencia artificial 1207 Investigación operativa 120704 Distribución y transporte 1299 otras especialidades matemáticas (especificar) |
Palabras clave: | Bin packing problem Capacitated vehicle routing Logistics Optimization Problem with time windows, et al. |
Fecha de publicación: | 2016 | Publicación seriada: | Decision Science Letters | Resumen: | This paper analyzes the integration of two combinatorial problems that frequently arise in production and distribution systems. One is the Bin Packing Problem (BPP) problem, which involves finding an ordering of some objects of different volumes to be packed into the minimal number of containers of the same or different size. An optimal solution to this NP-Hard problem can be approximated by means of meta-heuristic methods. On the other hand, we consider the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW), which is a variant of the Travelling Salesman Problem (again a NP-Hard problem) with extra constraints. Here we model those two problems in a single framework and use an evolutionary meta-heuristics to solve them jointly. Furthermore, we use data from a real world company as a test-bed for the method introduced here. | URI: | http://hdl.handle.net/10553/43618 | ISSN: | 1929-5804 | DOI: | 10.5267/j.dsl.2015.10.002 | Fuente: | Decision Science Letters [ISSN 1929-5804], v. 5, p. 317-326 |
Colección: | Artículos |
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