Comparing PSO and NSGA II for the biobjective Oil Derivatives Distribution Problem

Author

de Souza, Thatiana C N ; Goldbarg, Elizabeth F G ; Goldbarg, Marco C.

Author_Institution

Fed. Univ. of Rio Grande do Norte, Natal, Brazil

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

7

Abstract

This paper presents an experimental analysis of three algorithms for the Oil Derivatives Distribution Problem with two objectives. The problem consists in scheduling the transmission of oil products from source nodes to terminals in due times. The minimization of two objectives is considered: delivery time and fragmentation, that is, the consecutive transmission of distinct products in the same polyduct. The performance of a Particle Swarm Optimization algorithm is compared to the performance of two versions of the NSGA II algorithm in a set of 15 instances. The results show that the Particle Swarm algorithm outperforms the NSGA II.

Keywords

genetic algorithms; minimisation; particle swarm optimisation; petroleum industry; scheduling; NSGA II algorithm; PSO; biobjective oil derivatives distribution problem; delivery time; experimental analysis; fragmentation; minimization; oil products transmission; particle swarm optimization algorithm; scheduling; source nodes; Algorithm design and analysis; Biological cells; Minimization; Optimization; Petroleum; Planning; Production;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2010 IEEE Congress on

Conference_Location

Barcelona

Print_ISBN

978-1-4244-6909-3

Type

conf

DOI

10.1109/CEC.2010.5586556

Filename

5586556