Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43618
Title: Integrating packing and distribution problems and optimization through mathematical programming
Authors: Miguel, Fabio
Frutos, Mariano
Tohmé, Fernando
Méndez, Máximo 
UNESCO Clasification: 120304 Inteligencia artificial
1207 Investigación operativa
120704 Distribución y transporte
1299 otras especialidades matemáticas (especificar)
Keywords: Bin packing problem
Capacitated vehicle routing
Logistics
Optimization
Problem with time windows, et al
Issue Date: 2016
Journal: Decision Science Letters 
Abstract: 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
Source: Decision Science Letters [ISSN 1929-5804], v. 5, p. 317-326
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