A Multi-objective Genetic Algorithm with Relative Distance: Method, Performance Measures and Constraint Handling

Author

Tripathi, Praveen Kumar ; Bandyopadhyay, Sanghamitra ; Pal, Sankar Kumar

Author_Institution

Machine Intelligence Unit, Indian Stat. Inst., Calcutta

fYear

2007

fDate

5-7 March 2007

Firstpage

315

Lastpage

319

Abstract

A novel multi-objective evolutionary algorithm (MOEA), called multi-objective genetic algorithm with relative distance (MOGARD) is described. A novel relative distance parameter that ensures convergence to the Pareto optimal front and a nearest neighbour based method for maintaining diversity in the non-dominated set is used. Two novel performance measures are formulated to estimate the performance of the MOEAs. A penalty based constraint handling concept is introduced in MOGARD, for handling constraints. Experimental results demonstrate the superiority of MOGARD on several test problems, as compared to other recent and well known algorithms

Keywords

Pareto optimisation; genetic algorithms; Pareto optimal front; multiobjective evolutionary algorithm; multiobjective genetic algorithm; nearest neighbour based method; penalty based constraint handling; relative distance parameter; Biological cells; Computer applications; Convergence; Diversity methods; Euclidean distance; Evolutionary computation; Genetic algorithms; Machine intelligence; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing: Theory and Applications, 2007. ICCTA '07. International Conference on

Conference_Location

Kolkata

Print_ISBN

0-7695-2770-1

Type

conf

DOI

10.1109/ICCTA.2007.13

Filename

4127388