PGA/MOEAD: a preference-guided evolutionary algorithm for multi-objective decision-making problems with interval-valued fuzzy preferences

2017 ◽  
Vol 49 (3) ◽  
pp. 595-616 ◽  
Author(s):  
Bin Luo ◽  
Lin Lin ◽  
ShiSheng Zhong
Keyword(s):  
Decision Making ◽  
Evolutionary Algorithm ◽  
Multi Objective ◽  
Fuzzy Preferences ◽  
Interval Valued

Knee based multimodal multi-objective evolutionary algorithm for decision making

2021 ◽  
Vol 544 ◽  
pp. 39-55
Author(s):  
Kai Zhang ◽  
Chaonan Shen ◽  
Juanjuan He ◽  
Gary G. Yen
Keyword(s):  
Decision Making ◽  
Evolutionary Algorithm ◽  
Multi Objective

A Novel Multi-Objective Evolutionary Algorithm for Portfolio Selection

2013 ◽  
Vol 347-350 ◽  
pp. 3128-3132
Author(s):  
Lin Feng Huang
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Evolutionary Algorithm ◽  
Portfolio Selection ◽  
Knapsack Problem ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Portfolio Problem ◽  
The Relationship ◽  
Portfolio Return

Portfolio selection is a problem arising in finance and economics. While its basic formulations can be efficiently solved using linear or quadratic programming, its more practical variants have to be tackled by heuristics in many cases. In this work, both portfolio return and risk factors need to be considered, so it is abstracted as a multi-objective 0/1 knapsack problem and solved by a novel multi-objective evolutionary algorithm based on SPEA2. Experimental results show that the multi-objective optimization to solve the portfolio problem can better reveal the relationship between benefits and risks, to provide investors with a better basis for decision making.

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