This paper proposed a knee-point- driven multi-objective algorithm to solve the flexible job shop scheduling problem (FJSP). Experimental results show that the proposed method can not only obtain better results but also help decrease the selecting pressure for decision-makers compared to traditional ...
Time series forecasting by neural networks: a knee point~based multi~objective evolutionary algorithm approach [ J ] . Expert Systems with Applicationsꎬ2014ꎬ41(7) : 8049 - 8061.Du W, Leung SYS, Kwong CK (2014) Time series forecasting by neural networks: A knee point- based multi...
Many evolutionary algorithms (EAs) can’t select the solution which can accelerate the convergence to the Pareto front and maintain the diversity from a group of non-dominant solutions in the late stage of searching. In this article, the method of finding knee point is embedded in the process...
exoskeleton mechanism design, which simplifies the human knee joint into a 1-DOF revolute joint. When aligning the rotation axis of the human-machine joint, when viewed in the sagittal plane, the operation is to align the "point alignment point" between the exoskeleton rotation center point and ...
However, problems of decreased population diversity and uniformity of solutions distribution in the late evolutionary period is existed in the algorithm. Hence, this paper proposes a knee point-driven MOAF (kpMOAF) optimization algorithm to address the vulnerability of MOAF optimization algorithm. Knee...
Additionally, the convergence of the knee point approach can be exploited, and the subpopulation-based approach improves performance by improving the diversity of the evolutionary algorithm. Therefore, these advantages can make the algorithm suitable for solving MaOPs. Experimental results show that the ...
To this end, this paper proposes a multi-level knee point based multi-objective evolutionary algorithm (named MKnEA-AUC) for AUC maximization on the basis of a recently developed knee point driven evolutionary algorithm for multi/many-objective optimization. In MKnEA-AUC, an adaptive clustering ...
To be specific, the knee pointbased reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary alg...
Zhang X, Tian Y, Jin Y (2015) A knee point-driven evolution- ary algorithm for many-objective optimization. IEEE Trans Evol Comput 19(6):761-776Zhang, X., Tian, Y., Jin, Y.: A knee point-driven evolutionary algorithm for many-objective optimiza- tion. IEEE Transactions on Evolutionary...
MULTIOBJECTIVE EVOLUTIONARY ALGORITHMCOLONYThe number of solutions obtained is too large to provide a set of solutions with good performance in the nearby area of the true Pareto front when problem-specific preferences are unavailable. Therefore, this paper proposes a knee point-driven many-objective ...