Paper Info
Title
Constraint handling within MOEA/D through an additional scalarizing function
Abstract
ABSTRACTThe Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) has shown high-performance levels when solving complicated multi-objective optimization problems. However, its adaptation for dealing with constrained multi-objective optimization problems (cMOPs) keeps being under the scope of recent investigations. This paper introduces a novel selection mechanism inspired by the ε-constraint method, which builds a bi-objective problem considering the scalarizing function (used into the decomposition approach of MOEA/D) and the constraint violation degree as an objective function. During the selection step of MOEA/D, the scalarizing function is considered to choose the best solutions to the cMOP. Preliminary results obtained over a set of complicated test problems drawn from the CF test suite indicate that the proposed algorithm is highly competitive regarding state-of-the-art MOEAs adopted in our comparative study.
Year
DOI
Venue
2020
10.1145/3377930.3390240
Genetic and Evolutionary Computation Conference
Keywords
DocType
Citations 
Constrained handling techniques, multi-objective evolutionary algorithms, decomposition approach, scalarizing functions
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Saúl Zapotecas Martínez116716.46
Antonin Ponsich200.34