Pharmaceutical Routes Optimization using Artificial Intelligence Techniques

Author

Curcio, Duilio ; Longo, Francesco ; Mirabelli, Giovanni ; Papoff, Enrico

Author_Institution

Calabria Univ., Rende

fYear

2007

fDate

6-8 Sept. 2007

Firstpage

238

Lastpage

242

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IDAACS.2007.4488412

Filename

4488412