Title :
Pharmaceutical Routes Optimization using Artificial Intelligence Techniques
Author :
Curcio, Duilio ; Longo, Francesco ; Mirabelli, Giovanni ; Papoff, Enrico
Author_Institution :
Calabria Univ., Rende
Abstract :
The focus of this paper is to analyze the supply chain routes by means of artificial intelligence techniques for reducing transportation costs. The simulation model, built in eM-Plant, is used to implement two different approaches based on the ants theory and the genetic algorithms. A comparison of results is made in order to identify the better approach to adopt for the optimization process.
Keywords :
artificial intelligence; genetic algorithms; pharmaceutical industry; supply chain management; transportation; ants theory; artificial intelligence; eM-Plant; genetic algorithm; optimization; pharmaceutical routes; supply chain; transportation cost reduction; Analytical models; Artificial intelligence; Costs; Genetic algorithms; Logistics; Pharmaceuticals; Production; Supply chain management; Supply chains; Transportation; Ants Theory; Artificial Intelligence; Genetic Algorithms; Modeling; Routes Optimization; Simulation; Supply Chain Management;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2007. IDAACS 2007. 4th IEEE Workshop on
Conference_Location :
Dortmund
Print_ISBN :
978-1-4244-1347-8
Electronic_ISBN :
978-1-4244-1348-5
DOI :
10.1109/IDAACS.2007.4488412
