Optimal path in dynamic and stochastic networks

Author

Berradia, Tahar ; Mouzna, Joseph

Author_Institution

Instrum., Comput. Sci. & Syst., IRSEEM- ESIGELEC, St. Etienne du Rouvray, France

fYear

2009

fDate

4-7 Oct. 2009

Firstpage

1

Lastpage

6

Abstract

In transportation, the path finding problem is usually defined as the shortest path (SP) problem in deterministic terms (distance, deterministic cost, etc.). However, in real life situation, many information are uncertainty (travel time, travel cost or combination of criteria). In this paper we present a formulation for the multi-objective paths problem in dynamic and stochastic networks. In order to solve this problem a procedure integrating stochastic simulation and genetic algorithm proposed by Chen in [15] is applied and some numerical examples are given to validate our idea.

Keywords

genetic algorithms; graph theory; network theory (graphs); stochastic processes; transportation; SP problem; deterministic term; dynamic network; genetic algorithm; optimal multiobjective path finding problem; shortest path problem; stochastic network; stochastic simulation; transportation problem; travel cost criteria; travel time criteria; Computer science; Cost function; Genetic algorithms; Intelligent networks; Intelligent transportation systems; Shortest path problem; Stochastic processes; USA Councils; Uncertainty; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Transportation Systems, 2009. ITSC '09. 12th International IEEE Conference on

Conference_Location

St. Louis, MO

Print_ISBN

978-1-4244-5519-5

Electronic_ISBN

978-1-4244-5520-1

Type

conf

DOI

10.1109/ITSC.2009.5309878

Filename

5309878