Artículos de revistas
Integrating packing and distribution problems and optimization through mathematical programming
Fecha
2016-10Registro en:
Miguel, Fabio Maximiliano; Frutos, Mariano; Tohmé, Fernando Abel; Méndez, Máximo; Integrating packing and distribution problems and optimization through mathematical programming; Growing Science; Decision Science Letters; 5; 2; 10-2016; 317-326
1929-5804
CONICET Digital
CONICET
Autor
Miguel, Fabio Maximiliano
Frutos, Mariano
Tohmé, Fernando Abel
Méndez, Máximo
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.