A new idea for addressing multi-objective combinatorial optimization: Quantum multi-agent evolutionary algorithms

2009 ◽  
Author(s):  
Dongming Zhao ◽  
Fei Tao
Keyword(s):  
Combinatorial Optimization ◽  
Evolutionary Algorithms ◽  
Multi Objective ◽  
Multi Agent

Approach for Negotiation Problems in Multi-Agent Systems for DC Micro Grid Using Multi-Objective Evolutionary Algorithms

2015 ◽  
Vol 713-715 ◽  
pp. 2106-2109
Author(s):  
Mauricio Mauledoux ◽  
Edilberto Mejía-Ruda ◽  
Oscar I. Caldas
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Algorithms ◽  
Pareto Optimal ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Objective ◽  
Multi Agent ◽  
Micro Grid ◽  
Optimal Space ◽  
Multi Agents

The work is devoted to solve allocation task problem in multi agents systems using multi-objective genetic algorithms and comparing the technique with methods used in game theories. The paper shows the main advantages of genetic algorithms and the way to apply a parallel approach dividing the population in sub-populations saving time in the search and expanding the coverage of the solution in the Pareto optimal space.

QMAEA: A quantum multi-agent evolutionary algorithm for multi-objective combinatorial optimization

SIMULATION ◽  
2013 ◽  
Vol 90 (2) ◽  
pp. 182-204 ◽  
Author(s):  
F Tao ◽  
Y J Laili ◽  
L Zhang ◽  
Z H Zhang ◽  
AY C Nee
Keyword(s):  
Combinatorial Optimization ◽  
Evolutionary Algorithm ◽  
Multi Objective ◽  
Multi Agent
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