Abstract. MOEA/D is a novel and successful Multi-Objective Evolutionary Algorithms(MOEA) which utilizes the idea of problem decomposition to tackle the complexity from multiple obj...
Wudong Liu, Qingfu Zhang, Edward P. K. Tsang, Cao ...
The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the real system, remains a critical issue in Evolutionary Robotics (ER); it p...
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Abstract. Archives are used in Multi-Objective Evolutionary Algorithms to establish elitism. Depending on the optimization problem, an unconstrained archive may grow to an immense ...
An open problem in multiobjective optimization using the Pareto optimality criteria, is how to evaluate the performance of different evolutionary algorithms that solve multi– o...