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
miniatura
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