Paper Info
Title
A Multi-objective Genetic Algorithm with Relative Distance: Method, Performance Measures and Constraint Handling
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.
Year
DOI
Venue
2007
10.1109/ICCTA.2007.13
ICCTA
Keywords
Field
DocType
Pareto optimisation,genetic algorithms,Pareto optimal front,multiobjective evolutionary algorithm,multiobjective genetic algorithm,nearest neighbour based method,penalty based constraint handling,relative distance parameter
Convergence (routing),Nearest neighbour,Mathematical optimization,Evolutionary algorithm,Pattern recognition,Computer science,Pareto optimal,Artificial intelligence,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
0-7695-2770-1
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Praveen Kumar Tripathi117911.83
Sanghamitra Bandyopadhyay23977222.92
Sankar K. Pal36410627.31