Use of Reference Point Sets in a Decomposition-Based Multi-Objective Evolutionary Algorithm

2018 ◽  
pp. 372-383
Author(s):  
Edgar Manoatl Lopez ◽  
Carlos A. Coello Coello
Keyword(s):  
Evolutionary Algorithm ◽  
Reference Point ◽  
Point Sets ◽  
Multi Objective

A Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

2009 ◽  
Vol 17 (3) ◽  
pp. 411-436 ◽  
Author(s):  
Lothar Thiele ◽  
Kaisa Miettinen ◽  
Pekka J. Korhonen ◽  
Julian Molina
Keyword(s):  
Evolutionary Algorithm ◽  
Reference Point ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Preference Information ◽  
Multi Objective ◽  
Pareto Optimal Set ◽  
Interactive Algorithm ◽  
Aspiration Levels ◽  
Optimal Set

In this paper, we discuss the idea of incorporating preference information into evolutionary multi-objective optimization and propose a preference-based evolutionary approach that can be used as an integral part of an interactive algorithm. One algorithm is proposed in the paper. At each iteration, the decision maker is asked to give preference information in terms of his or her reference point consisting of desirable aspiration levels for objective functions. The information is used in an evolutionary algorithm to generate a new population by combining the fitness function and an achievement scalarizing function. In multi-objective optimization, achievement scalarizing functions are widely used to project a given reference point into the Pareto optimal set. In our approach, the next population is thus more concentrated in the area where more preferred alternatives are assumed to lie and the whole Pareto optimal set does not have to be generated with equal accuracy. The approach is demonstrated by numerical examples.

Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

Informatica ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Ernestas Filatovas ◽  
Olga Kurasova ◽  
Karthik Sindhya
Keyword(s):  
Evolutionary Algorithm ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective
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