Search Results - "Dynamic multi-objective optimisation algorithm"

Analysing the performance of dynamic multi-objective optimisation algorithms

Authors: Helbig, M Engelbrecht, AP

Subject Terms: Dynamic multi-objective optimisation problems, DMOOP, Dynamic multi-objective optimisation algorithm, DMOA

File Description: application/pdf

Relation: Workflow;11367; http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6557744; http://hdl.handle.net/10204/6945

Availability: http://hdl.handle.net/10204/6945
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6557744

Special Issue "Model Predictive Control: Algorithms and Applications": Foreword by the Guest Editor.

Authors: Ławryńczuk, Maciej

Source: Algorithms; Dec2022, Vol. 15 Issue 12, p452, 3p

Subject Terms: PREDICTION models, ALGORITHMS, ARTIFICIAL neural networks, MONTE Carlo method, EULER equations (Rigid dynamics)

Using Headless Chicken Crossover for Local Guide Selection When Solving Dynamic Multi-objective Optimization.

Authors: Helbig, Mardé Engelbrecht, Andries P.

Source: Advances in Nature & Biologically Inspired Computing; 2016, p381-392, 12p

Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems.

Authors: Joćko, Paweł Ombuki-Berman, Beatrice M. Engelbrecht, Andries P.

Source: Swarm Intelligence; Jun2022, Vol. 16 Issue 2, p143-168, 26p

Influence of the archive size on the performance of the dynamic vector evaluated particle swarm optimisation algorithm solving dynamic multi-objective optimisation problems.

Authors: Helbig, Marde Engelbrecht, Andries

Source: 2015 IEEE Congress on Evolutionary Computation (CEC); 2015, p1926-1933, 8p

Heterogeneous dynamic vector evaluated particle swarm optimisation for dynamic multi-objective optimisation.

Authors: Helbig, Marde Engelbrecht, Andries P.

Source: 2014 IEEE Congress on Evolutionary Computation (CEC); 2014, p3151-3159, 9p

Analysing the performance of dynamic multi-objective optimisation algorithms.

Authors: Helbig, Marde Engelbrecht, Andries P.

Source: 2013 IEEE Congress on Evolutionary Computation; 2013, p1531-1539, 9p

Advances in Nature and Biologically Inspired Computing

Authors: Nelishia Pillay Andries P. Engelbrecht Ajith Abraham et al.

Resource Type: eBook.

Subjects: Artificial intelligence, Computer science, Natural computation, Computational intelligence

Categories: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General)