Results 1 to 10 of about 156,769 (285)
Hyperspectral image compressed processing: Evolutionary multi-objective optimization sparse decomposition. [PDF]
PLoS ONE, 2022 In the compressed processing of hyperspectral images, orthogonal matching pursuit algorithm (OMP) can be used to obtain sparse decomposition results.
Li Wang, Wei Wang
doaj +2 more sources
Multi-objective multi-criteria evolutionary algorithm for multi-objective multi-task optimization
Complex & Intelligent Systems, 2022 Evolutionary multi-objective multi-task optimization is an emerging paradigm for solving multi-objective multi-task optimization problem (MO-MTOP) using evolutionary computation.
Ke-Jing Du +3 more
doaj +1 more source
Current trends in evolutionary multi-objective optimization [PDF]
International Journal for Simulation and Multidisciplinary Design Optimization, 2007 In a short span of about 14 years, evolutionary multi-objective optimization (EMO) has established itself as a mature field of research and application with an extensive literature, many commercial softwares, numerous freely downloadable codes, a ...
Deb Kalyanmoy
doaj +1 more source
International Journal of Computational Intelligence Systems, 2022 The constrained optimization problems can be transformed into multi-objective optimization problems, and thus can be optimized by multi-objective evolutionary algorithms.
Xinsheng Lai
doaj +1 more source
Evolutionary Game Theory in Multi-Objective Optimization Problem [PDF]
International Journal of Computational Intelligence Systems, 2010 Multi-objective optimization focuses on simultaneous optimization of multiple targets. Evolutionary game theory transforms the optimization problem into game strategic problem and using adaptable dynamic game evolution process intelligently obtains the ...
Maozhu Jin, Xia Lei, Jian Du
doaj +1 more source
Mathematical and Computational Applications, 2022 Multi-objective evolutionary algorithms (MOEAs) have been successfully applied for the numerical treatment of multi-objective optimization problems (MOP) during the last three decades.
Carlos Ignacio Hernández Castellanos +1 more
doaj +1 more source
Methods That Optimize Multi-Objective Problems: A Survey and Experimental Evaluation
IEEE Access, 2020 Most current multi-optimization survey papers classify methods into broad objective categories and do not draw clear boundaries between the specific techniques employed by these methods.
Kamal Taha
doaj +1 more source
Evolutionary multi-objective network optimization algorithm in trajectory planning
Ain Shams Engineering Journal, 2021 Flight network optimization, one of the airspace planning challenges, effectively manages airspace resources toward increasing airspace capacity and reducing air traffic congestion.
Mostafa Borhani
doaj +1 more source
A constrained multi-objective surrogate-based optimization algorithm [PDF]
, 2014 Surrogate models or metamodels are widely used in the realm of engineering for design optimization to minimize the number of computationally expensive simulations.
Couckuyt, Ivo +3 more
core +1 more source
Solution Representation Learning in Multi-Objective Transfer Evolutionary Optimization
IEEE Access, 2021 This paper presents a first study on solution representation learning for inducing greater alignment and hence positive transfers between distinct multi-objective optimization tasks that bear discrepancies in their original search spaces.
Ray Lim +4 more
doaj +1 more source